--- _id: '15009' author: - first_name: Nico full_name: Epple, Nico last_name: Epple - first_name: Simone full_name: Dari, Simone last_name: Dari - first_name: Ludwig full_name: Drees, Ludwig last_name: Drees - first_name: Valentin full_name: Protschky, Valentin last_name: Protschky - first_name: Andreas full_name: Riener, Andreas last_name: Riener citation: ama: 'Epple N, Dari S, Drees L, Protschky V, Riener A. Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries. In: 2019 IEEE Intelligent Vehicles Symposium (IV). ; 2019. doi:10.1109/ivs.2019.8814100' apa: Epple, N., Dari, S., Drees, L., Protschky, V., & Riener, A. (2019). Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries. In 2019 IEEE Intelligent Vehicles Symposium (IV). https://doi.org/10.1109/ivs.2019.8814100 bibtex: '@inproceedings{Epple_Dari_Drees_Protschky_Riener_2019, title={Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries}, DOI={10.1109/ivs.2019.8814100}, booktitle={2019 IEEE Intelligent Vehicles Symposium (IV)}, author={Epple, Nico and Dari, Simone and Drees, Ludwig and Protschky, Valentin and Riener, Andreas}, year={2019} }' chicago: Epple, Nico, Simone Dari, Ludwig Drees, Valentin Protschky, and Andreas Riener. “Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries.” In 2019 IEEE Intelligent Vehicles Symposium (IV), 2019. https://doi.org/10.1109/ivs.2019.8814100. ieee: N. Epple, S. Dari, L. Drees, V. Protschky, and A. Riener, “Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries,” in 2019 IEEE Intelligent Vehicles Symposium (IV), 2019. mla: Epple, Nico, et al. “Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries.” 2019 IEEE Intelligent Vehicles Symposium (IV), 2019, doi:10.1109/ivs.2019.8814100. short: 'N. Epple, S. Dari, L. Drees, V. Protschky, A. Riener, in: 2019 IEEE Intelligent Vehicles Symposium (IV), 2019.' date_created: 2019-11-15T10:54:04Z date_updated: 2022-01-06T06:52:14Z department: - _id: '34' - _id: '355' doi: 10.1109/ivs.2019.8814100 language: - iso: eng publication: 2019 IEEE Intelligent Vehicles Symposium (IV) publication_identifier: isbn: - '9781728105604' publication_status: published status: public title: Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries type: conference user_id: '315' year: '2019' ... --- _id: '15011' author: - first_name: Alexander full_name: Tornede, Alexander id: '38209' last_name: Tornede - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking. In: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019. KIT Scientific Publishing, Karlsruhe; 2019:135-146.' apa: 'Tornede, A., Wever, M. D., & Hüllermeier, E. (2019). Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking. In F. Hoffmann, E. Hüllermeier, & R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019 (pp. 135–146). Dortmund: KIT Scientific Publishing, Karlsruhe.' bibtex: '@inproceedings{Tornede_Wever_Hüllermeier_2019, title={Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking}, booktitle={Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019}, publisher={KIT Scientific Publishing, Karlsruhe}, author={Tornede, Alexander and Wever, Marcel Dominik and Hüllermeier, Eyke}, editor={Hoffmann, Frank and Hüllermeier, Eyke and Mikut, RalfEditors}, year={2019}, pages={135–146} }' chicago: 'Tornede, Alexander, Marcel Dominik Wever, and Eyke Hüllermeier. “Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking.” In Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, edited by Frank Hoffmann, Eyke Hüllermeier, and Ralf Mikut, 135–46. KIT Scientific Publishing, Karlsruhe, 2019.' ieee: 'A. Tornede, M. D. Wever, and E. Hüllermeier, “Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking,” in Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, Dortmund, 2019, pp. 135–146.' mla: 'Tornede, Alexander, et al. “Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking.” Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, edited by Frank Hoffmann et al., KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–46.' short: 'A. Tornede, M.D. Wever, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–146.' conference: end_date: 2019-11-29 location: Dortmund name: 29. Workshop Computational Intelligence start_date: 2019-11-28 date_created: 2019-11-15T13:29:25Z date_updated: 2022-01-06T06:52:14Z ddc: - '006' department: - _id: '355' editor: - first_name: Frank full_name: Hoffmann, Frank last_name: Hoffmann - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: Ralf full_name: Mikut, Ralf last_name: Mikut file: - access_level: open_access content_type: application/pdf creator: ahetzer date_created: 2020-05-25T08:01:31Z date_updated: 2020-05-25T08:01:31Z file_id: '17060' file_name: ci_workshop_tornede.pdf file_size: 468825 relation: main_file file_date_updated: 2020-05-25T08:01:31Z has_accepted_license: '1' language: - iso: eng oa: '1' page: 135-146 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019 publication_identifier: isbn: - 978-3-7315-0979-0 publication_status: published publisher: KIT Scientific Publishing, Karlsruhe status: public title: 'Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking' type: conference user_id: '38209' year: '2019' ... --- _id: '15013' author: - first_name: Klaus full_name: Brinker, Klaus last_name: Brinker - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Brinker K, Hüllermeier E. A Reduction of Label Ranking to Multiclass Classification. In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases. Würzburg, Germany; 2019.' apa: Brinker, K., & Hüllermeier, E. (2019). A Reduction of Label Ranking to Multiclass Classification. In Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases. Würzburg, Germany. bibtex: '@inproceedings{Brinker_Hüllermeier_2019, place={Würzburg, Germany}, title={A Reduction of Label Ranking to Multiclass Classification}, booktitle={Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases}, author={Brinker, Klaus and Hüllermeier, Eyke}, year={2019} }' chicago: Brinker, Klaus, and Eyke Hüllermeier. “A Reduction of Label Ranking to Multiclass Classification.” In Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases. Würzburg, Germany, 2019. ieee: K. Brinker and E. Hüllermeier, “A Reduction of Label Ranking to Multiclass Classification,” in Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, 2019. mla: Brinker, Klaus, and Eyke Hüllermeier. “A Reduction of Label Ranking to Multiclass Classification.” Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, 2019. short: 'K. Brinker, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Würzburg, Germany, 2019.' date_created: 2019-11-18T07:26:43Z date_updated: 2022-01-06T06:52:14Z department: - _id: '34' - _id: '355' - _id: '7' language: - iso: eng place: Würzburg, Germany publication: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases status: public title: A Reduction of Label Ranking to Multiclass Classification type: conference user_id: '315' year: '2019' ... --- _id: '15014' author: - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Ines full_name: Couso, Ines last_name: Couso - first_name: Sebastian full_name: Diestercke, Sebastian last_name: Diestercke citation: ama: 'Hüllermeier E, Couso I, Diestercke S. Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants. In: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management. ; 2019.' apa: 'Hüllermeier, E., Couso, I., & Diestercke, S. (2019). Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants. In Proceedings SUM 2019, International Conference on Scalable Uncertainty Management.' bibtex: '@inproceedings{Hüllermeier_Couso_Diestercke_2019, title={Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants}, booktitle={Proceedings SUM 2019, International Conference on Scalable Uncertainty Management}, author={Hüllermeier, Eyke and Couso, Ines and Diestercke, Sebastian}, year={2019} }' chicago: 'Hüllermeier, Eyke, Ines Couso, and Sebastian Diestercke. “Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants.” In Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.' ieee: 'E. Hüllermeier, I. Couso, and S. Diestercke, “Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants,” in Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.' mla: 'Hüllermeier, Eyke, et al. “Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants.” Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.' short: 'E. Hüllermeier, I. Couso, S. Diestercke, in: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.' date_created: 2019-11-18T07:38:13Z date_updated: 2022-01-06T06:52:14Z department: - _id: '34' - _id: '355' - _id: '7' language: - iso: eng publication: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management status: public title: 'Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants' type: conference user_id: '315' year: '2019' ... --- _id: '15015' author: - first_name: Sascha full_name: Henzgen, Sascha last_name: Henzgen - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: Henzgen S, Hüllermeier E. Mining Rank Data. ACM Transactions on Knowledge Discovery from Data. 2019:1-36. doi:10.1145/3363572 apa: Henzgen, S., & Hüllermeier, E. (2019). Mining Rank Data. ACM Transactions on Knowledge Discovery from Data, 1–36. https://doi.org/10.1145/3363572 bibtex: '@article{Henzgen_Hüllermeier_2019, title={Mining Rank Data}, DOI={10.1145/3363572}, journal={ACM Transactions on Knowledge Discovery from Data}, author={Henzgen, Sascha and Hüllermeier, Eyke}, year={2019}, pages={1–36} }' chicago: Henzgen, Sascha, and Eyke Hüllermeier. “Mining Rank Data.” ACM Transactions on Knowledge Discovery from Data, 2019, 1–36. https://doi.org/10.1145/3363572. ieee: S. Henzgen and E. Hüllermeier, “Mining Rank Data,” ACM Transactions on Knowledge Discovery from Data, pp. 1–36, 2019. mla: Henzgen, Sascha, and Eyke Hüllermeier. “Mining Rank Data.” ACM Transactions on Knowledge Discovery from Data, 2019, pp. 1–36, doi:10.1145/3363572. short: S. Henzgen, E. Hüllermeier, ACM Transactions on Knowledge Discovery from Data (2019) 1–36. date_created: 2019-11-18T07:40:27Z date_updated: 2022-01-06T06:52:14Z department: - _id: '34' - _id: '355' - _id: '7' doi: 10.1145/3363572 language: - iso: eng page: 1-36 publication: ACM Transactions on Knowledge Discovery from Data publication_identifier: issn: - 1556-4681 publication_status: published status: public title: Mining Rank Data type: journal_article user_id: '315' year: '2019' ... --- _id: '14027' author: - first_name: Viktor full_name: Bengs, Viktor id: '76599' last_name: Bengs - first_name: Matthias full_name: Eulert, Matthias last_name: Eulert - first_name: Hajo full_name: Holzmann, Hajo last_name: Holzmann citation: ama: Bengs V, Eulert M, Holzmann H. Asymptotic confidence sets for the jump curve in bivariate regression problems. Journal of Multivariate Analysis. 2019:291-312. doi:10.1016/j.jmva.2019.02.017 apa: Bengs, V., Eulert, M., & Holzmann, H. (2019). Asymptotic confidence sets for the jump curve in bivariate regression problems. Journal of Multivariate Analysis, 291–312. https://doi.org/10.1016/j.jmva.2019.02.017 bibtex: '@article{Bengs_Eulert_Holzmann_2019, title={Asymptotic confidence sets for the jump curve in bivariate regression problems}, DOI={10.1016/j.jmva.2019.02.017}, journal={Journal of Multivariate Analysis}, author={Bengs, Viktor and Eulert, Matthias and Holzmann, Hajo}, year={2019}, pages={291–312} }' chicago: Bengs, Viktor, Matthias Eulert, and Hajo Holzmann. “Asymptotic Confidence Sets for the Jump Curve in Bivariate Regression Problems.” Journal of Multivariate Analysis, 2019, 291–312. https://doi.org/10.1016/j.jmva.2019.02.017. ieee: V. Bengs, M. Eulert, and H. Holzmann, “Asymptotic confidence sets for the jump curve in bivariate regression problems,” Journal of Multivariate Analysis, pp. 291–312, 2019. mla: Bengs, Viktor, et al. “Asymptotic Confidence Sets for the Jump Curve in Bivariate Regression Problems.” Journal of Multivariate Analysis, 2019, pp. 291–312, doi:10.1016/j.jmva.2019.02.017. short: V. Bengs, M. Eulert, H. Holzmann, Journal of Multivariate Analysis (2019) 291–312. date_created: 2019-10-30T14:22:57Z date_updated: 2022-01-06T06:51:52Z department: - _id: '34' - _id: '355' doi: 10.1016/j.jmva.2019.02.017 language: - iso: eng page: 291-312 publication: Journal of Multivariate Analysis publication_identifier: issn: - 0047-259X publication_status: published status: public title: Asymptotic confidence sets for the jump curve in bivariate regression problems type: journal_article user_id: '76599' year: '2019' ... --- _id: '14028' author: - first_name: Viktor full_name: Bengs, Viktor id: '76599' last_name: Bengs - first_name: Hajo full_name: Holzmann, Hajo last_name: Holzmann citation: ama: Bengs V, Holzmann H. Adaptive confidence sets for kink estimation. Electronic Journal of Statistics. 2019:1523-1579. doi:10.1214/19-ejs1555 apa: Bengs, V., & Holzmann, H. (2019). Adaptive confidence sets for kink estimation. Electronic Journal of Statistics, 1523–1579. https://doi.org/10.1214/19-ejs1555 bibtex: '@article{Bengs_Holzmann_2019, title={Adaptive confidence sets for kink estimation}, DOI={10.1214/19-ejs1555}, journal={Electronic Journal of Statistics}, author={Bengs, Viktor and Holzmann, Hajo}, year={2019}, pages={1523–1579} }' chicago: Bengs, Viktor, and Hajo Holzmann. “Adaptive Confidence Sets for Kink Estimation.” Electronic Journal of Statistics, 2019, 1523–79. https://doi.org/10.1214/19-ejs1555. ieee: V. Bengs and H. Holzmann, “Adaptive confidence sets for kink estimation,” Electronic Journal of Statistics, pp. 1523–1579, 2019. mla: Bengs, Viktor, and Hajo Holzmann. “Adaptive Confidence Sets for Kink Estimation.” Electronic Journal of Statistics, 2019, pp. 1523–79, doi:10.1214/19-ejs1555. short: V. Bengs, H. Holzmann, Electronic Journal of Statistics (2019) 1523–1579. date_created: 2019-10-30T14:25:16Z date_updated: 2022-01-06T06:51:52Z department: - _id: '34' - _id: '355' doi: 10.1214/19-ejs1555 language: - iso: eng page: 1523-1579 publication: Electronic Journal of Statistics publication_identifier: issn: - 1935-7524 publication_status: published status: public title: Adaptive confidence sets for kink estimation type: journal_article user_id: '76599' year: '2019' ... --- _id: '13132' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Alexander full_name: Tornede, Alexander id: '38209' last_name: Tornede - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Mohr F, Wever MD, Tornede A, Hüllermeier E. From Automated to On-The-Fly Machine Learning. In: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft. INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik. Bonn: Gesellschaft für Informatik e.V.; 2019:273-274.' apa: 'Mohr, F., Wever, M. D., Tornede, A., & Hüllermeier, E. (2019). From Automated to On-The-Fly Machine Learning. In INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft (pp. 273–274). Bonn: Gesellschaft für Informatik e.V.' bibtex: '@inproceedings{Mohr_Wever_Tornede_Hüllermeier_2019, place={Bonn}, series={INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik}, title={From Automated to On-The-Fly Machine Learning}, booktitle={INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft}, publisher={Gesellschaft für Informatik e.V.}, author={Mohr, Felix and Wever, Marcel Dominik and Tornede, Alexander and Hüllermeier, Eyke}, year={2019}, pages={273–274}, collection={INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik} }' chicago: 'Mohr, Felix, Marcel Dominik Wever, Alexander Tornede, and Eyke Hüllermeier. “From Automated to On-The-Fly Machine Learning.” In INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, 273–74. INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft Für Informatik. Bonn: Gesellschaft für Informatik e.V., 2019.' ieee: 'F. Mohr, M. D. Wever, A. Tornede, and E. Hüllermeier, “From Automated to On-The-Fly Machine Learning,” in INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, Kassel, 2019, pp. 273–274.' mla: 'Mohr, Felix, et al. “From Automated to On-The-Fly Machine Learning.” INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, Gesellschaft für Informatik e.V., 2019, pp. 273–74.' short: 'F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, in: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, Gesellschaft für Informatik e.V., Bonn, 2019, pp. 273–274.' conference: end_date: 2019-09-26 location: Kassel name: Informatik 2019 start_date: 2019-09-23 date_created: 2019-09-04T08:44:46Z date_updated: 2022-01-06T06:51:28Z department: - _id: '355' language: - iso: eng page: ' 273-274 ' place: Bonn project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publication: 'INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft' publisher: Gesellschaft für Informatik e.V. series_title: INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik status: public title: From Automated to On-The-Fly Machine Learning type: conference_abstract user_id: '38209' year: '2019' ... --- _id: '10232' abstract: - lang: eng text: Existing tools for automated machine learning, such as Auto-WEKA, TPOT, auto-sklearn, and more recently ML-Plan, have shown impressive results for the tasks of single-label classification and regression. Yet, there is only little work on other types of machine learning problems so far. In particular, there is almost no work on automating the engineering of machine learning solutions for multi-label classification (MLC). We show how the scope of ML-Plan, an AutoML-tool for multi-class classification, can be extended towards MLC using MEKA, which is a multi-label extension of the well-known Java library WEKA. The resulting approach recursively refines MEKA's multi-label classifiers, nesting other multi-label classifiers for meta algorithms and single-label classifiers provided by WEKA as base learners. In our evaluation, we find that the proposed approach yields strong results and performs significantly better than a set of baselines we compare with. author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Alexander full_name: Tornede, Alexander id: '38209' last_name: Tornede - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Wever MD, Mohr F, Tornede A, Hüllermeier E. Automating Multi-Label Classification Extending ML-Plan. In: ; 2019.' apa: Wever, M. D., Mohr, F., Tornede, A., & Hüllermeier, E. (2019). Automating Multi-Label Classification Extending ML-Plan. Presented at the 6th ICML Workshop on Automated Machine Learning (AutoML 2019), Long Beach, CA, USA. bibtex: '@inproceedings{Wever_Mohr_Tornede_Hüllermeier_2019, title={Automating Multi-Label Classification Extending ML-Plan}, author={Wever, Marcel Dominik and Mohr, Felix and Tornede, Alexander and Hüllermeier, Eyke}, year={2019} }' chicago: Wever, Marcel Dominik, Felix Mohr, Alexander Tornede, and Eyke Hüllermeier. “Automating Multi-Label Classification Extending ML-Plan,” 2019. ieee: M. D. Wever, F. Mohr, A. Tornede, and E. Hüllermeier, “Automating Multi-Label Classification Extending ML-Plan,” presented at the 6th ICML Workshop on Automated Machine Learning (AutoML 2019), Long Beach, CA, USA, 2019. mla: Wever, Marcel Dominik, et al. Automating Multi-Label Classification Extending ML-Plan. 2019. short: 'M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.' conference: end_date: 2019-06-15 location: Long Beach, CA, USA name: 6th ICML Workshop on Automated Machine Learning (AutoML 2019) start_date: 2019-06-09 date_created: 2019-06-11T21:33:06Z date_updated: 2022-01-06T06:50:33Z ddc: - '006' department: - _id: '355' file: - access_level: open_access content_type: application/pdf creator: wever date_created: 2019-09-10T08:19:01Z date_updated: 2019-09-10T08:20:44Z file_id: '13177' file_name: Automating_MultiLabel_Classification_Extending_ML-Plan.pdf file_size: 388191 relation: main_file file_date_updated: 2019-09-10T08:20:44Z has_accepted_license: '1' language: - iso: eng oa: '1' project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing status: public title: Automating Multi-Label Classification Extending ML-Plan type: conference user_id: '33176' year: '2019' ... --- _id: '20243' author: - first_name: Katharina full_name: Rohlfing, Katharina id: '50352' last_name: Rohlfing - first_name: Giuseppe full_name: Leonardi, Giuseppe last_name: Leonardi - first_name: Iris full_name: Nomikou, Iris last_name: Nomikou - first_name: Joanna full_name: Rączaszek-Leonardi, Joanna last_name: Rączaszek-Leonardi - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Rohlfing K, Leonardi G, Nomikou I, Rączaszek-Leonardi J, Hüllermeier E. Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches. IEEE Transactions on Cognitive and Developmental Systems. Published online 2019. doi:10.1109/TCDS.2019.2892991' apa: 'Rohlfing, K., Leonardi, G., Nomikou, I., Rączaszek-Leonardi, J., & Hüllermeier, E. (2019). Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches. IEEE Transactions on Cognitive and Developmental Systems. https://doi.org/10.1109/TCDS.2019.2892991' bibtex: '@article{Rohlfing_Leonardi_Nomikou_Rączaszek-Leonardi_Hüllermeier_2019, title={Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches}, DOI={10.1109/TCDS.2019.2892991}, journal={IEEE Transactions on Cognitive and Developmental Systems}, author={Rohlfing, Katharina and Leonardi, Giuseppe and Nomikou, Iris and Rączaszek-Leonardi, Joanna and Hüllermeier, Eyke}, year={2019} }' chicago: 'Rohlfing, Katharina, Giuseppe Leonardi, Iris Nomikou, Joanna Rączaszek-Leonardi, and Eyke Hüllermeier. “Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches.” IEEE Transactions on Cognitive and Developmental Systems, 2019. https://doi.org/10.1109/TCDS.2019.2892991.' ieee: 'K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, and E. Hüllermeier, “Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches,” IEEE Transactions on Cognitive and Developmental Systems, 2019, doi: 10.1109/TCDS.2019.2892991.' mla: 'Rohlfing, Katharina, et al. “Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches.” IEEE Transactions on Cognitive and Developmental Systems, 2019, doi:10.1109/TCDS.2019.2892991.' short: K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, E. Hüllermeier, IEEE Transactions on Cognitive and Developmental Systems (2019). date_created: 2020-11-02T13:25:49Z date_updated: 2023-02-01T12:39:19Z department: - _id: '749' - _id: '355' doi: 10.1109/TCDS.2019.2892991 language: - iso: eng publication: IEEE Transactions on Cognitive and Developmental Systems status: public title: 'Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches' type: journal_article user_id: '14931' year: '2019' ... --- _id: '2479' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Amin full_name: Faez, Amin last_name: Faez citation: ama: 'Mohr F, Wever MD, Hüllermeier E, Faez A. (WIP) Towards the Automated Composition of Machine Learning Services. In: SCC. San Francisco, CA, USA: IEEE; 2018. doi:10.1109/SCC.2018.00039' apa: 'Mohr, F., Wever, M. D., Hüllermeier, E., & Faez, A. (2018). (WIP) Towards the Automated Composition of Machine Learning Services. In SCC. San Francisco, CA, USA: IEEE. https://doi.org/10.1109/SCC.2018.00039' bibtex: '@inproceedings{Mohr_Wever_Hüllermeier_Faez_2018, place={San Francisco, CA, USA}, title={(WIP) Towards the Automated Composition of Machine Learning Services}, DOI={10.1109/SCC.2018.00039}, booktitle={SCC}, publisher={IEEE}, author={Mohr, Felix and Wever, Marcel Dominik and Hüllermeier, Eyke and Faez, Amin}, year={2018} }' chicago: 'Mohr, Felix, Marcel Dominik Wever, Eyke Hüllermeier, and Amin Faez. “(WIP) Towards the Automated Composition of Machine Learning Services.” In SCC. San Francisco, CA, USA: IEEE, 2018. https://doi.org/10.1109/SCC.2018.00039.' ieee: F. Mohr, M. D. Wever, E. Hüllermeier, and A. Faez, “(WIP) Towards the Automated Composition of Machine Learning Services,” in SCC, San Francisco, CA, USA, 2018. mla: Mohr, Felix, et al. “(WIP) Towards the Automated Composition of Machine Learning Services.” SCC, IEEE, 2018, doi:10.1109/SCC.2018.00039. short: 'F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: SCC, IEEE, San Francisco, CA, USA, 2018.' conference: end_date: 2018-07-07 location: San Francisco, CA, USA name: IEEE International Conference on Services Computing, SCC 2018 start_date: 2018-07-02 date_created: 2018-04-24T08:34:52Z date_updated: 2022-01-06T06:56:35Z ddc: - '000' department: - _id: '355' doi: 10.1109/SCC.2018.00039 file: - access_level: closed content_type: application/pdf creator: wever date_created: 2018-11-06T15:08:39Z date_updated: 2018-11-06T15:08:39Z file_id: '5382' file_name: 08456425.pdf file_size: 237890 relation: main_file file_date_updated: 2018-11-06T15:08:39Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://ieeexplore.ieee.org/document/8456425 oa: '1' place: San Francisco, CA, USA project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publication: SCC publication_status: published publisher: IEEE status: public title: (WIP) Towards the Automated Composition of Machine Learning Services type: conference user_id: '49109' year: '2018' ... --- _id: '19524' abstract: - lang: eng text: "Object ranking is an important problem in the realm of preference learning.\r\nOn the basis of training data in the form of a set of rankings of objects,\r\nwhich are typically represented as feature vectors, the goal is to learn a\r\nranking function that predicts a linear order of any new set of objects.\r\nCurrent approaches commonly focus on ranking by scoring, i.e., on learning an\r\nunderlying latent utility function that seeks to capture the inherent utility\r\nof each object. These approaches, however, are not able to take possible\r\neffects of context-dependence into account, where context-dependence means that\r\nthe utility or usefulness of an object may also depend on what other objects\r\nare available as alternatives. In this paper, we formalize the problem of\r\ncontext-dependent ranking and present two general approaches based on two\r\nnatural representations of context-dependent ranking functions. Both approaches\r\nare instantiated by means of appropriate neural network architectures, which\r\nare evaluated on suitable benchmark task." author: - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt - first_name: Pritha full_name: Gupta, Pritha last_name: Gupta - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier citation: ama: Pfannschmidt K, Gupta P, Hüllermeier E. Deep Architectures for Learning Context-dependent Ranking Functions. arXiv:180305796. 2018. apa: Pfannschmidt, K., Gupta, P., & Hüllermeier, E. (2018). Deep Architectures for Learning Context-dependent Ranking Functions. ArXiv:1803.05796. bibtex: '@article{Pfannschmidt_Gupta_Hüllermeier_2018, title={Deep Architectures for Learning Context-dependent Ranking Functions}, journal={arXiv:1803.05796}, author={Pfannschmidt, Karlson and Gupta, Pritha and Hüllermeier, Eyke}, year={2018} }' chicago: Pfannschmidt, Karlson, Pritha Gupta, and Eyke Hüllermeier. “Deep Architectures for Learning Context-Dependent Ranking Functions.” ArXiv:1803.05796, 2018. ieee: K. Pfannschmidt, P. Gupta, and E. Hüllermeier, “Deep Architectures for Learning Context-dependent Ranking Functions,” arXiv:1803.05796. 2018. mla: Pfannschmidt, Karlson, et al. “Deep Architectures for Learning Context-Dependent Ranking Functions.” ArXiv:1803.05796, 2018. short: K. Pfannschmidt, P. Gupta, E. Hüllermeier, ArXiv:1803.05796 (2018). date_created: 2020-09-17T10:53:39Z date_updated: 2022-01-06T06:54:06Z department: - _id: '7' - _id: '355' language: - iso: eng project: - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: arXiv:1803.05796 status: public title: Deep Architectures for Learning Context-dependent Ranking Functions type: preprint user_id: '13472' year: '2018' ... --- _id: '2857' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Theodor full_name: Lettmann, Theodor id: '315' last_name: Lettmann orcid: 0000-0001-5859-2457 - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' citation: ama: 'Mohr F, Lettmann T, Hüllermeier E, Wever MD. Programmatic Task Network Planning. In: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning. AAAI; 2018:31-39.' apa: 'Mohr, F., Lettmann, T., Hüllermeier, E., & Wever, M. D. (2018). Programmatic Task Network Planning. In Proceedings of the 1st ICAPS Workshop on Hierarchical Planning (pp. 31–39). Delft, Netherlands: AAAI.' bibtex: '@inproceedings{Mohr_Lettmann_Hüllermeier_Wever_2018, title={Programmatic Task Network Planning}, booktitle={Proceedings of the 1st ICAPS Workshop on Hierarchical Planning}, publisher={AAAI}, author={Mohr, Felix and Lettmann, Theodor and Hüllermeier, Eyke and Wever, Marcel Dominik}, year={2018}, pages={31–39} }' chicago: Mohr, Felix, Theodor Lettmann, Eyke Hüllermeier, and Marcel Dominik Wever. “Programmatic Task Network Planning.” In Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, 31–39. AAAI, 2018. ieee: F. Mohr, T. Lettmann, E. Hüllermeier, and M. D. Wever, “Programmatic Task Network Planning,” in Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, Delft, Netherlands, 2018, pp. 31–39. mla: Mohr, Felix, et al. “Programmatic Task Network Planning.” Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39. short: 'F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.' conference: end_date: 2018-06-29 location: Delft, Netherlands name: 28th International Conference on Automated Planning and Scheduling start_date: 2018-06-24 date_created: 2018-05-24T09:00:20Z date_updated: 2022-01-06T06:58:08Z ddc: - '000' department: - _id: '355' file: - access_level: closed content_type: application/pdf creator: wever date_created: 2018-11-06T15:18:26Z date_updated: 2018-11-06T15:18:26Z file_id: '5384' file_name: Mohr18ProgrammaticPlanning.pdf file_size: 349958 relation: main_file success: 1 file_date_updated: 2018-11-06T15:18:26Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://icaps18.icaps-conference.org/fileadmin/alg/conferences/icaps18/workshops/workshop08/docs/Mohr18ProgrammaticPlanning.pdf oa: '1' page: 31-39 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publication: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning publisher: AAAI status: public title: Programmatic Task Network Planning type: conference user_id: '315' year: '2018' ... --- _id: '24150' author: - first_name: Arunselvan full_name: Ramaswamy, Arunselvan id: '66937' last_name: Ramaswamy orcid: https://orcid.org/ 0000-0001-7547-8111 - first_name: Shalabh full_name: Bhatnagar, Shalabh last_name: Bhatnagar citation: ama: Ramaswamy A, Bhatnagar S. Stability of stochastic approximations with “controlled markov” noise and temporal difference learning. IEEE Transactions on Automatic Control. 2018;64(6):2614-2620. apa: Ramaswamy, A., & Bhatnagar, S. (2018). Stability of stochastic approximations with “controlled markov” noise and temporal difference learning. IEEE Transactions on Automatic Control, 64(6), 2614–2620. bibtex: '@article{Ramaswamy_Bhatnagar_2018, title={Stability of stochastic approximations with “controlled markov” noise and temporal difference learning}, volume={64}, number={6}, journal={IEEE Transactions on Automatic Control}, publisher={IEEE}, author={Ramaswamy, Arunselvan and Bhatnagar, Shalabh}, year={2018}, pages={2614–2620} }' chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stability of Stochastic Approximations with ‘Controlled Markov’ Noise and Temporal Difference Learning.” IEEE Transactions on Automatic Control 64, no. 6 (2018): 2614–20.' ieee: A. Ramaswamy and S. Bhatnagar, “Stability of stochastic approximations with ‘controlled markov’ noise and temporal difference learning,” IEEE Transactions on Automatic Control, vol. 64, no. 6, pp. 2614–2620, 2018. mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stability of Stochastic Approximations with ‘Controlled Markov’ Noise and Temporal Difference Learning.” IEEE Transactions on Automatic Control, vol. 64, no. 6, IEEE, 2018, pp. 2614–20. short: A. Ramaswamy, S. Bhatnagar, IEEE Transactions on Automatic Control 64 (2018) 2614–2620. date_created: 2021-09-10T10:17:54Z date_updated: 2022-01-06T06:56:08Z department: - _id: '355' intvolume: ' 64' issue: '6' language: - iso: eng page: 2614-2620 publication: IEEE Transactions on Automatic Control publisher: IEEE status: public title: Stability of stochastic approximations with “controlled markov” noise and temporal difference learning type: journal_article user_id: '66937' volume: 64 year: '2018' ... --- _id: '24151' author: - first_name: Burak full_name: Demirel, Burak last_name: Demirel - first_name: Arunselvan full_name: Ramaswamy, Arunselvan id: '66937' last_name: Ramaswamy orcid: https://orcid.org/ 0000-0001-7547-8111 - first_name: Daniel E full_name: Quevedo, Daniel E last_name: Quevedo - first_name: Holger full_name: Karl, Holger last_name: Karl citation: ama: 'Demirel B, Ramaswamy A, Quevedo DE, Karl H. Deepcas: A deep reinforcement learning algorithm for control-aware scheduling. IEEE Control Systems Letters. 2018;2(4):737-742.' apa: 'Demirel, B., Ramaswamy, A., Quevedo, D. E., & Karl, H. (2018). Deepcas: A deep reinforcement learning algorithm for control-aware scheduling. IEEE Control Systems Letters, 2(4), 737–742.' bibtex: '@article{Demirel_Ramaswamy_Quevedo_Karl_2018, title={Deepcas: A deep reinforcement learning algorithm for control-aware scheduling}, volume={2}, number={4}, journal={IEEE Control Systems Letters}, publisher={IEEE}, author={Demirel, Burak and Ramaswamy, Arunselvan and Quevedo, Daniel E and Karl, Holger}, year={2018}, pages={737–742} }' chicago: 'Demirel, Burak, Arunselvan Ramaswamy, Daniel E Quevedo, and Holger Karl. “Deepcas: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling.” IEEE Control Systems Letters 2, no. 4 (2018): 737–42.' ieee: 'B. Demirel, A. Ramaswamy, D. E. Quevedo, and H. Karl, “Deepcas: A deep reinforcement learning algorithm for control-aware scheduling,” IEEE Control Systems Letters, vol. 2, no. 4, pp. 737–742, 2018.' mla: 'Demirel, Burak, et al. “Deepcas: A Deep Reinforcement Learning Algorithm for Control-Aware Scheduling.” IEEE Control Systems Letters, vol. 2, no. 4, IEEE, 2018, pp. 737–42.' short: B. Demirel, A. Ramaswamy, D.E. Quevedo, H. Karl, IEEE Control Systems Letters 2 (2018) 737–742. date_created: 2021-09-10T10:19:07Z date_updated: 2022-01-06T06:56:08Z department: - _id: '355' intvolume: ' 2' issue: '4' language: - iso: eng page: 737-742 publication: IEEE Control Systems Letters publisher: IEEE status: public title: 'Deepcas: A deep reinforcement learning algorithm for control-aware scheduling' type: journal_article user_id: '66937' volume: 2 year: '2018' ... --- _id: '2471' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Mohr F, Wever MD, Hüllermeier E. On-The-Fly Service Construction with Prototypes. In: SCC. San Francisco, CA, USA: IEEE Computer Society; 2018. doi:10.1109/SCC.2018.00036' apa: 'Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). On-The-Fly Service Construction with Prototypes. In SCC. San Francisco, CA, USA: IEEE Computer Society. https://doi.org/10.1109/SCC.2018.00036' bibtex: '@inproceedings{Mohr_Wever_Hüllermeier_2018, place={San Francisco, CA, USA}, title={On-The-Fly Service Construction with Prototypes}, DOI={10.1109/SCC.2018.00036}, booktitle={SCC}, publisher={IEEE Computer Society}, author={Mohr, Felix and Wever, Marcel Dominik and Hüllermeier, Eyke}, year={2018} }' chicago: 'Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “On-The-Fly Service Construction with Prototypes.” In SCC. San Francisco, CA, USA: IEEE Computer Society, 2018. https://doi.org/10.1109/SCC.2018.00036.' ieee: F. Mohr, M. D. Wever, and E. Hüllermeier, “On-The-Fly Service Construction with Prototypes,” in SCC, San Francisco, CA, USA, 2018. mla: Mohr, Felix, et al. “On-The-Fly Service Construction with Prototypes.” SCC, IEEE Computer Society, 2018, doi:10.1109/SCC.2018.00036. short: 'F. Mohr, M.D. Wever, E. Hüllermeier, in: SCC, IEEE Computer Society, San Francisco, CA, USA, 2018.' conference: end_date: 2018-07-07 location: San Francisco, CA, USA name: IEEE International Conference on Services Computing, SCC 2018 start_date: 2018-07-02 date_created: 2018-04-23T11:40:20Z date_updated: 2022-01-06T06:56:32Z ddc: - '000' department: - _id: '355' doi: 10.1109/SCC.2018.00036 file: - access_level: closed content_type: application/pdf creator: wever date_created: 2018-11-06T15:15:38Z date_updated: 2018-11-06T15:15:38Z file_id: '5383' file_name: 08456422.pdf file_size: 356132 relation: main_file success: 1 file_date_updated: 2018-11-06T15:15:38Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://ieeexplore.ieee.org/abstract/document/8456422 oa: '1' place: San Francisco, CA, USA project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publication: SCC publisher: IEEE Computer Society status: public title: On-The-Fly Service Construction with Prototypes type: conference user_id: '49109' year: '2018' ... --- _id: '3402' abstract: - lang: eng text: In machine learning, so-called nested dichotomies are utilized as a reduction technique, i.e., to decompose a multi-class classification problem into a set of binary problems, which are solved using a simple binary classifier as a base learner. The performance of the (multi-class) classifier thus produced strongly depends on the structure of the decomposition. In this paper, we conduct an empirical study, in which we compare existing heuristics for selecting a suitable structure in the form of a nested dichotomy. Moreover, we propose two additional heuristics as natural completions. One of them is the Best-of-K heuristic, which picks the (presumably) best among K randomly generated nested dichotomies. Surprisingly, and in spite of its simplicity, it turns out to outperform the state of the art. author: - first_name: Vitalik full_name: Melnikov, Vitalik last_name: Melnikov - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Melnikov V, Hüllermeier E. On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis. Machine Learning. 2018. doi:10.1007/s10994-018-5733-1' apa: 'Melnikov, V., & Hüllermeier, E. (2018). On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis. Machine Learning. https://doi.org/10.1007/s10994-018-5733-1' bibtex: '@article{Melnikov_Hüllermeier_2018, title={On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis}, DOI={10.1007/s10994-018-5733-1}, journal={Machine Learning}, author={Melnikov, Vitalik and Hüllermeier, Eyke}, year={2018} }' chicago: 'Melnikov, Vitalik, and Eyke Hüllermeier. “On the Effectiveness of Heuristics for Learning Nested Dichotomies: An Empirical Analysis.” Machine Learning, 2018. https://doi.org/10.1007/s10994-018-5733-1.' ieee: 'V. Melnikov and E. Hüllermeier, “On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis,” Machine Learning, 2018.' mla: 'Melnikov, Vitalik, and Eyke Hüllermeier. “On the Effectiveness of Heuristics for Learning Nested Dichotomies: An Empirical Analysis.” Machine Learning, 2018, doi:10.1007/s10994-018-5733-1.' short: V. Melnikov, E. Hüllermeier, Machine Learning (2018). date_created: 2018-06-29T07:44:26Z date_updated: 2022-01-06T06:59:14Z ddc: - '000' department: - _id: '355' doi: 10.1007/s10994-018-5733-1 file: - access_level: closed content_type: application/pdf creator: ups date_created: 2018-11-02T15:30:57Z date_updated: 2018-11-02T15:30:57Z file_id: '5305' file_name: OnTheEffectivenessOfHeuristics.pdf file_size: 1482882 relation: main_file success: 1 file_date_updated: 2018-11-02T15:30:57Z has_accepted_license: '1' language: - iso: eng project: - _id: '11' name: SFB 901 - Subproject B3 - _id: '3' name: SFB 901 - Project Area B - _id: '1' name: SFB 901 publication: Machine Learning publication_identifier: issn: - 1573-0565 status: public title: 'On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis' type: journal_article user_id: '15504' year: '2018' ... --- _id: '3510' abstract: - lang: eng text: Automated machine learning (AutoML) seeks to automatically select, compose, and parametrize machine learning algorithms, so as to achieve optimal performance on a given task (dataset). Although current approaches to AutoML have already produced impressive results, the field is still far from mature, and new techniques are still being developed. In this paper, we present ML-Plan, a new approach to AutoML based on hierarchical planning. To highlight the potential of this approach, we compare ML-Plan to the state-of-the-art frameworks Auto-WEKA, auto-sklearn, and TPOT. In an extensive series of experiments, we show that ML-Plan is highly competitive and often outperforms existing approaches. article_type: original author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Mohr F, Wever MD, Hüllermeier E. ML-Plan: Automated Machine Learning via Hierarchical Planning. Machine Learning. Published online 2018:1495-1515. doi:10.1007/s10994-018-5735-z' apa: 'Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). ML-Plan: Automated Machine Learning via Hierarchical Planning. Machine Learning, 1495–1515. https://doi.org/10.1007/s10994-018-5735-z' bibtex: '@article{Mohr_Wever_Hüllermeier_2018, title={ML-Plan: Automated Machine Learning via Hierarchical Planning}, DOI={10.1007/s10994-018-5735-z}, journal={Machine Learning}, publisher={Springer}, author={Mohr, Felix and Wever, Marcel Dominik and Hüllermeier, Eyke}, year={2018}, pages={1495–1515} }' chicago: 'Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “ML-Plan: Automated Machine Learning via Hierarchical Planning.” Machine Learning, 2018, 1495–1515. https://doi.org/10.1007/s10994-018-5735-z.' ieee: 'F. Mohr, M. D. Wever, and E. Hüllermeier, “ML-Plan: Automated Machine Learning via Hierarchical Planning,” Machine Learning, pp. 1495–1515, 2018, doi: 10.1007/s10994-018-5735-z.' mla: 'Mohr, Felix, et al. “ML-Plan: Automated Machine Learning via Hierarchical Planning.” Machine Learning, Springer, 2018, pp. 1495–515, doi:10.1007/s10994-018-5735-z.' short: F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018) 1495–1515. conference: end_date: 2018-09-14 location: Dublin, Ireland name: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases start_date: 2018-09-10 date_created: 2018-07-08T14:06:14Z date_updated: 2022-01-06T06:59:21Z ddc: - '000' department: - _id: '355' - _id: '34' - _id: '7' - _id: '26' doi: 10.1007/s10994-018-5735-z file: - access_level: closed content_type: application/pdf creator: ups date_created: 2018-11-02T15:32:16Z date_updated: 2018-11-02T15:32:16Z file_id: '5306' file_name: ML-PlanAutomatedMachineLearnin.pdf file_size: 1070937 relation: main_file success: 1 file_date_updated: 2018-11-02T15:32:16Z has_accepted_license: '1' keyword: - AutoML - Hierarchical Planning - HTN planning - ML-Plan language: - iso: eng main_file_link: - open_access: '1' url: https://rdcu.be/3Nc2 oa: '1' page: 1495-1515 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Machine Learning publication_identifier: eissn: - 1573-0565 issn: - 0885-6125 publication_status: epub_ahead publisher: Springer status: public title: 'ML-Plan: Automated Machine Learning via Hierarchical Planning' type: journal_article user_id: '5786' year: '2018' ... --- _id: '3552' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Mohr F, Wever MD, Hüllermeier E. Reduction Stumps for Multi-Class Classification. In: Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch, the Netherlands. doi:10.1007/978-3-030-01768-2_19' apa: Mohr, F., Wever, M. D., & Hüllermeier, E. (n.d.). Reduction Stumps for Multi-Class Classification. In Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch, the Netherlands. https://doi.org/10.1007/978-3-030-01768-2_19 bibtex: '@inproceedings{Mohr_Wever_Hüllermeier, place={‘s-Hertogenbosch, the Netherlands}, title={Reduction Stumps for Multi-Class Classification}, DOI={10.1007/978-3-030-01768-2_19}, booktitle={Proceedings of the Symposium on Intelligent Data Analysis}, author={Mohr, Felix and Wever, Marcel Dominik and Hüllermeier, Eyke} }' chicago: Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Reduction Stumps for Multi-Class Classification.” In Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch, the Netherlands, n.d. https://doi.org/10.1007/978-3-030-01768-2_19. ieee: F. Mohr, M. D. Wever, and E. Hüllermeier, “Reduction Stumps for Multi-Class Classification,” in Proceedings of the Symposium on Intelligent Data Analysis, ‘s-Hertogenbosch, the Netherlands. mla: Mohr, Felix, et al. “Reduction Stumps for Multi-Class Classification.” Proceedings of the Symposium on Intelligent Data Analysis, doi:10.1007/978-3-030-01768-2_19. short: 'F. Mohr, M.D. Wever, E. Hüllermeier, in: Proceedings of the Symposium on Intelligent Data Analysis, ‘s-Hertogenbosch, the Netherlands, n.d.' conference: end_date: 2018-10-26 location: ‘s-Hertogenbosch, the Netherlands name: Symposium on Intelligent Data Analysis start_date: 2018-10-24 date_created: 2018-07-13T15:29:15Z date_updated: 2022-01-06T06:59:25Z ddc: - '000' department: - _id: '355' doi: 10.1007/978-3-030-01768-2_19 file: - access_level: closed content_type: application/pdf creator: wever date_created: 2018-11-06T15:23:02Z date_updated: 2018-11-06T15:23:02Z file_id: '5385' file_name: Mohr2018_Chapter_ReductionStumpsForMulti-classC.pdf file_size: 1348768 relation: main_file success: 1 file_date_updated: 2018-11-06T15:23:02Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://link.springer.com/chapter/10.1007%2F978-3-030-01768-2_19 oa: '1' place: ‘s-Hertogenbosch, the Netherlands project: - _id: '1' name: SFB 901 - _id: '10' name: SFB 901 - Subproject B2 - _id: '3' name: SFB 901 - Project Area B publication: Proceedings of the Symposium on Intelligent Data Analysis publication_status: accepted quality_controlled: '1' status: public title: Reduction Stumps for Multi-Class Classification type: conference user_id: '49109' year: '2018' ... --- _id: '3852' abstract: - lang: eng text: "In automated machine learning (AutoML), the process of engineering machine learning applications with respect to a specific problem is (partially) automated.\r\nVarious AutoML tools have already been introduced to provide out-of-the-box machine learning functionality.\r\nMore specifically, by selecting machine learning algorithms and optimizing their hyperparameters, these tools produce a machine learning pipeline tailored to the problem at hand.\r\nExcept for TPOT, all of these tools restrict the maximum number of processing steps of such a pipeline.\r\nHowever, as TPOT follows an evolutionary approach, it suffers from performance issues when dealing with larger datasets.\r\nIn this paper, we present an alternative approach leveraging a hierarchical planning to configure machine learning pipelines that are unlimited in length.\r\nWe evaluate our approach and find its performance to be competitive with other AutoML tools, including TPOT." author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Wever MD, Mohr F, Hüllermeier E. ML-Plan for Unlimited-Length Machine Learning Pipelines. In: ICML 2018 AutoML Workshop. ; 2018.' apa: Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). ML-Plan for Unlimited-Length Machine Learning Pipelines. In ICML 2018 AutoML Workshop. Stockholm, Sweden. bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2018, title={ML-Plan for Unlimited-Length Machine Learning Pipelines}, booktitle={ICML 2018 AutoML Workshop}, author={Wever, Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2018} }' chicago: Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “ML-Plan for Unlimited-Length Machine Learning Pipelines.” In ICML 2018 AutoML Workshop, 2018. ieee: M. D. Wever, F. Mohr, and E. Hüllermeier, “ML-Plan for Unlimited-Length Machine Learning Pipelines,” in ICML 2018 AutoML Workshop, Stockholm, Sweden, 2018. mla: Wever, Marcel Dominik, et al. “ML-Plan for Unlimited-Length Machine Learning Pipelines.” ICML 2018 AutoML Workshop, 2018. short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: ICML 2018 AutoML Workshop, 2018.' conference: end_date: 2018-07-15 location: Stockholm, Sweden name: ICML 2018 AutoML Workshop start_date: 2018-07-10 date_created: 2018-08-09T06:14:54Z date_updated: 2022-01-06T06:59:46Z ddc: - '006' department: - _id: '355' file: - access_level: open_access content_type: application/pdf creator: wever date_created: 2018-08-09T06:14:43Z date_updated: 2018-08-09T06:14:43Z file_id: '3853' file_name: 38.pdf file_size: 297811 relation: main_file file_date_updated: 2018-08-09T06:14:43Z has_accepted_license: '1' keyword: - automated machine learning - complex pipelines - hierarchical planning language: - iso: eng main_file_link: - url: https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxhdXRvbWwyMDE4aWNtbHxneDo3M2Q3MjUzYjViNDRhZTAx oa: '1' project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publication: ICML 2018 AutoML Workshop quality_controlled: '1' status: public title: ML-Plan for Unlimited-Length Machine Learning Pipelines type: conference urn: '38527' user_id: '49109' year: '2018' ... --- _id: '2109' abstract: - lang: eng text: In multinomial classification, reduction techniques are commonly used to decompose the original learning problem into several simpler problems. For example, by recursively bisecting the original set of classes, so-called nested dichotomies define a set of binary classification problems that are organized in the structure of a binary tree. In contrast to the existing one-shot heuristics for constructing nested dichotomies and motivated by recent work on algorithm configuration, we propose a genetic algorithm for optimizing the structure of such dichotomies. A key component of this approach is the proposed genetic representation that facilitates the application of standard genetic operators, while still supporting the exchange of partial solutions under recombination. We evaluate the approach in an extensive experimental study, showing that it yields classifiers with superior generalization performance. author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Wever MD, Mohr F, Hüllermeier E. Ensembles of Evolved Nested Dichotomies for Classification. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto, Japan: ACM; 2018. doi:10.1145/3205455.3205562' apa: 'Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). Ensembles of Evolved Nested Dichotomies for Classification. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto, Japan: ACM. https://doi.org/10.1145/3205455.3205562' bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2018, place={Kyoto, Japan}, title={Ensembles of Evolved Nested Dichotomies for Classification}, DOI={10.1145/3205455.3205562}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018}, publisher={ACM}, author={Wever, Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2018} }' chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Ensembles of Evolved Nested Dichotomies for Classification.” In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto, Japan: ACM, 2018. https://doi.org/10.1145/3205455.3205562.' ieee: M. D. Wever, F. Mohr, and E. Hüllermeier, “Ensembles of Evolved Nested Dichotomies for Classification,” in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, Kyoto, Japan, 2018. mla: Wever, Marcel Dominik, et al. “Ensembles of Evolved Nested Dichotomies for Classification.” Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, 2018, doi:10.1145/3205455.3205562. short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, Kyoto, Japan, 2018.' conference: end_date: 2018-07-19 location: Kyoto, Japan name: GECCO 2018 start_date: 2018-07-15 date_created: 2018-03-31T13:51:23Z date_updated: 2022-01-06T06:54:45Z ddc: - '000' department: - _id: '355' doi: 10.1145/3205455.3205562 file: - access_level: closed content_type: application/pdf creator: ups date_created: 2018-11-02T14:33:54Z date_updated: 2018-11-02T14:33:54Z file_id: '5275' file_name: p561-wever.pdf file_size: 875404 relation: main_file success: 1 file_date_updated: 2018-11-02T14:33:54Z has_accepted_license: '1' keyword: - Classification - Hierarchical Decomposition - Indirect Encoding language: - iso: eng main_file_link: - open_access: '1' url: https://dl.acm.org/citation.cfm?doid=3205455.3205562 oa: '1' place: Kyoto, Japan project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018 publication_status: published publisher: ACM status: public title: Ensembles of Evolved Nested Dichotomies for Classification type: conference user_id: '33176' year: '2018' ... --- _id: '17713' author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: Wever MD, Mohr F, Hüllermeier E. Automated Multi-Label Classification based on ML-Plan. Published online 2018. apa: Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). Automated Multi-Label Classification based on ML-Plan. Arxiv. bibtex: '@article{Wever_Mohr_Hüllermeier_2018, title={Automated Multi-Label Classification based on ML-Plan}, publisher={Arxiv}, author={Wever, Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2018} }' chicago: Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automated Multi-Label Classification Based on ML-Plan.” Arxiv, 2018. ieee: M. D. Wever, F. Mohr, and E. Hüllermeier, “Automated Multi-Label Classification based on ML-Plan.” Arxiv, 2018. mla: Wever, Marcel Dominik, et al. Automated Multi-Label Classification Based on ML-Plan. Arxiv, 2018. short: M.D. Wever, F. Mohr, E. Hüllermeier, (2018). date_created: 2020-08-07T11:38:10Z date_updated: 2022-01-06T06:53:17Z department: - _id: '34' - _id: '355' - _id: '26' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/pdf/1811.04060.pdf oa: '1' project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publisher: Arxiv status: public title: Automated Multi-Label Classification based on ML-Plan type: preprint user_id: '5786' year: '2018' ... --- _id: '17714' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: Mohr F, Wever MD, Hüllermeier E. Automated machine learning service composition. Published online 2018. apa: Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). Automated machine learning service composition. bibtex: '@article{Mohr_Wever_Hüllermeier_2018, title={Automated machine learning service composition}, author={Mohr, Felix and Wever, Marcel Dominik and Hüllermeier, Eyke}, year={2018} }' chicago: Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Automated Machine Learning Service Composition,” 2018. ieee: F. Mohr, M. D. Wever, and E. Hüllermeier, “Automated machine learning service composition.” 2018. mla: Mohr, Felix, et al. Automated Machine Learning Service Composition. 2018. short: F. Mohr, M.D. Wever, E. Hüllermeier, (2018). date_created: 2020-08-07T11:40:13Z date_updated: 2022-01-06T06:53:17Z department: - _id: '34' - _id: '355' - _id: '26' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/pdf/1809.00486.pdf oa: '1' project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing status: public title: Automated machine learning service composition type: preprint user_id: '5786' year: '2018' ... --- _id: '5693' author: - first_name: Helena full_name: Graf, Helena id: '52640' last_name: Graf citation: ama: Graf H. Ranking of Classification Algorithms in AutoML. Universität Paderborn; 2018. apa: Graf, H. (2018). Ranking of Classification Algorithms in AutoML. Universität Paderborn. bibtex: '@book{Graf_2018, title={Ranking of Classification Algorithms in AutoML}, publisher={Universität Paderborn}, author={Graf, Helena}, year={2018} }' chicago: Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018. ieee: H. Graf, Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018. mla: Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018. short: H. Graf, Ranking of Classification Algorithms in AutoML, Universität Paderborn, 2018. date_created: 2018-11-15T08:06:41Z date_updated: 2022-01-06T07:02:35Z department: - _id: '355' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publisher: Universität Paderborn status: public supervisor: - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier title: Ranking of Classification Algorithms in AutoML type: bachelorsthesis user_id: '33176' year: '2018' ... --- _id: '5936' author: - first_name: Manuel full_name: Scheibl, Manuel last_name: Scheibl citation: ama: Scheibl M. Learning about Learning Curves from Dataset Properties. Universität Paderborn; 2018. apa: Scheibl, M. (2018). Learning about learning curves from dataset properties. Universität Paderborn. bibtex: '@book{Scheibl_2018, title={Learning about learning curves from dataset properties}, publisher={Universität Paderborn}, author={Scheibl, Manuel}, year={2018} }' chicago: Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. Universität Paderborn, 2018. ieee: M. Scheibl, Learning about learning curves from dataset properties. Universität Paderborn, 2018. mla: Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. Universität Paderborn, 2018. short: M. Scheibl, Learning about Learning Curves from Dataset Properties, Universität Paderborn, 2018. date_created: 2018-11-28T10:29:53Z date_updated: 2022-01-06T07:02:47Z department: - _id: '355' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publisher: Universität Paderborn status: public supervisor: - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier title: Learning about learning curves from dataset properties type: bachelorsthesis user_id: '477' year: '2018' ... --- _id: '6423' author: - first_name: Dirk full_name: Schäfer, Dirk last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Discovery Science. Cham: Springer International Publishing; 2018:161-175. doi:10.1007/978-3-030-01771-2_11' apa: 'Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement Learning Using Dyad Ranking. In Discovery Science (pp. 161–175). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-01771-2_11' bibtex: '@inbook{Schäfer_Hüllermeier_2018, place={Cham}, title={Preference-Based Reinforcement Learning Using Dyad Ranking}, DOI={10.1007/978-3-030-01771-2_11}, booktitle={Discovery Science}, publisher={Springer International Publishing}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={161–175} }' chicago: 'Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” In Discovery Science, 161–75. Cham: Springer International Publishing, 2018. https://doi.org/10.1007/978-3-030-01771-2_11.' ieee: 'D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using Dyad Ranking,” in Discovery Science, Cham: Springer International Publishing, 2018, pp. 161–175.' mla: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” Discovery Science, Springer International Publishing, 2018, pp. 161–75, doi:10.1007/978-3-030-01771-2_11. short: 'D. Schäfer, E. Hüllermeier, in: Discovery Science, Springer International Publishing, Cham, 2018, pp. 161–175.' date_created: 2018-12-20T15:52:03Z date_updated: 2022-01-06T07:03:04Z ddc: - '000' department: - _id: '355' doi: 10.1007/978-3-030-01771-2_11 file: - access_level: closed content_type: application/pdf creator: ups date_created: 2019-01-11T11:03:50Z date_updated: 2019-01-11T11:03:50Z file_id: '6623' file_name: Schäfer-Hüllermeier2018_Chapter_Preference-BasedReinforcementL.pdf file_size: 458972 relation: main_file success: 1 file_date_updated: 2019-01-11T11:03:50Z has_accepted_license: '1' language: - iso: eng page: 161-175 place: Cham project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publication: Discovery Science publication_identifier: isbn: - '9783030017705' - '9783030017712' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer International Publishing status: public title: Preference-Based Reinforcement Learning Using Dyad Ranking type: book_chapter user_id: '49109' year: '2018' ... --- _id: '10591' alternative_title: - Manifesto from Dagstuhl Perspectives Workshop 16151 citation: ama: Abiteboul S, Arenas M, Barceló P, et al., eds. Research Directions for Principles of Data Management. Vol 7.; 2018:1-29. apa: Abiteboul, S., Arenas, M., Barceló, P., Bienvenu, M., Calvanese, D., David, C., … Yi, K. (Eds.). (2018). Research Directions for Principles of Data Management (Vol. 7, pp. 1–29). bibtex: '@book{Abiteboul_Arenas_Barceló_Bienvenu_Calvanese_David_Hull_Hüllermeier_Kimelfeld_Libkin_et al._2018, title={Research Directions for Principles of Data Management}, volume={7}, number={1}, year={2018}, pages={1–29} }' chicago: Abiteboul, S., M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, et al., eds. Research Directions for Principles of Data Management. Vol. 7, 2018. ieee: S. Abiteboul et al., Eds., Research Directions for Principles of Data Management, vol. 7, no. 1. 2018, pp. 1–29. mla: Abiteboul, S., et al., editors. Research Directions for Principles of Data Management. Vol. 7, no. 1, 2018, pp. 1–29. short: S. Abiteboul, M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, E. Hüllermeier, B. Kimelfeld, L. Libkin, W. Martens, T. Milo, F. Murlak, F. Neven, M. Ortiz, T. Schwentick, J. Stoyanovich, J. Su, D. Suciu, V. Vianu, K. Yi, eds., Research Directions for Principles of Data Management, 2018. date_created: 2019-07-09T15:58:12Z date_updated: 2022-01-06T06:50:45Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' editor: - first_name: S. full_name: Abiteboul, S. last_name: Abiteboul - first_name: M. full_name: Arenas, M. last_name: Arenas - first_name: P. full_name: Barceló, P. last_name: Barceló - first_name: M. full_name: Bienvenu, M. last_name: Bienvenu - first_name: D. full_name: Calvanese, D. last_name: Calvanese - first_name: C. full_name: David, C. last_name: David - first_name: R. full_name: Hull, R. last_name: Hull - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: B. full_name: Kimelfeld, B. last_name: Kimelfeld - first_name: L. full_name: Libkin, L. last_name: Libkin - first_name: W. full_name: Martens, W. last_name: Martens - first_name: T. full_name: Milo, T. last_name: Milo - first_name: F. full_name: Murlak, F. last_name: Murlak - first_name: F. full_name: Neven, F. last_name: Neven - first_name: M. full_name: Ortiz, M. last_name: Ortiz - first_name: T. full_name: Schwentick, T. last_name: Schwentick - first_name: J. full_name: Stoyanovich, J. last_name: Stoyanovich - first_name: J. full_name: Su, J. last_name: Su - first_name: D. full_name: Suciu, D. last_name: Suciu - first_name: V. full_name: Vianu, V. last_name: Vianu - first_name: K. full_name: Yi, K. last_name: Yi intvolume: ' 7' issue: '1' language: - iso: eng page: 1-29 status: public title: Research Directions for Principles of Data Management type: conference_editor user_id: '49109' volume: 7 year: '2018' ... --- _id: '10783' author: - first_name: Ines full_name: Couso, Ines last_name: Couso - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Couso I, Hüllermeier E. Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In: Mostaghim S, Nürnberger A, Borgelt C, eds. Frontiers in Computational Intelligence. Springer; 2018:31-46.' apa: 'Couso, I., & Hüllermeier, E. (2018). Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In S. Mostaghim, A. Nürnberger, & C. Borgelt (Eds.), Frontiers in Computational Intelligence (pp. 31–46). Springer.' bibtex: '@inbook{Couso_Hüllermeier_2018, title={Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators}, booktitle={Frontiers in Computational Intelligence}, publisher={Springer}, author={Couso, Ines and Hüllermeier, Eyke}, editor={Mostaghim, Sanaz and Nürnberger, Andreas and Borgelt, ChristianEditors}, year={2018}, pages={31–46} }' chicago: 'Couso, Ines, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Frontiers in Computational Intelligence, edited by Sanaz Mostaghim, Andreas Nürnberger, and Christian Borgelt, 31–46. Springer, 2018.' ieee: 'I. Couso and E. Hüllermeier, “Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators,” in Frontiers in Computational Intelligence, S. Mostaghim, A. Nürnberger, and C. Borgelt, Eds. Springer, 2018, pp. 31–46.' mla: 'Couso, Ines, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” Frontiers in Computational Intelligence, edited by Sanaz Mostaghim et al., Springer, 2018, pp. 31–46.' short: 'I. Couso, E. Hüllermeier, in: S. Mostaghim, A. Nürnberger, C. Borgelt (Eds.), Frontiers in Computational Intelligence, Springer, 2018, pp. 31–46.' date_created: 2019-07-10T15:39:00Z date_updated: 2022-01-06T06:50:50Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' editor: - first_name: Sanaz full_name: Mostaghim, Sanaz last_name: Mostaghim - first_name: Andreas full_name: Nürnberger, Andreas last_name: Nürnberger - first_name: Christian full_name: Borgelt, Christian last_name: Borgelt language: - iso: eng page: 31-46 publication: Frontiers in Computational Intelligence publisher: Springer status: public title: 'Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators' type: book_chapter user_id: '49109' year: '2018' ... --- _id: '16038' author: - first_name: D. full_name: Schäfer, D. last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: Schäfer D, Hüllermeier E. Dyad ranking using Plackett-Luce models based on joint feature representations. Machine Learning. 2018;107(5):903-941. apa: Schäfer, D., & Hüllermeier, E. (2018). Dyad ranking using Plackett-Luce models based on joint feature representations. Machine Learning, 107(5), 903–941. bibtex: '@article{Schäfer_Hüllermeier_2018, title={Dyad ranking using Plackett-Luce models based on joint feature representations}, volume={107}, number={5}, journal={Machine Learning}, author={Schäfer, D. and Hüllermeier, Eyke}, year={2018}, pages={903–941} }' chicago: 'Schäfer, D., and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning 107, no. 5 (2018): 903–41.' ieee: D. Schäfer and E. Hüllermeier, “Dyad ranking using Plackett-Luce models based on joint feature representations,” Machine Learning, vol. 107, no. 5, pp. 903–941, 2018. mla: Schäfer, D., and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning, vol. 107, no. 5, 2018, pp. 903–41. short: D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941. date_created: 2020-02-24T15:59:19Z date_updated: 2022-01-06T06:52:42Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' intvolume: ' 107' issue: '5' language: - iso: eng page: 903-941 publication: Machine Learning status: public title: Dyad ranking using Plackett-Luce models based on joint feature representations type: journal_article user_id: '49109' volume: 107 year: '2018' ... --- _id: '10145' author: - first_name: Mohsen full_name: Ahmadi Fahandar, Mohsen last_name: Ahmadi Fahandar - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Ahmadi Fahandar M, Hüllermeier E. Learning to Rank Based on Analogical Reasoning. In: Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI). ; 2018:2951-2958.' apa: Ahmadi Fahandar, M., & Hüllermeier, E. (2018). Learning to Rank Based on Analogical Reasoning. In Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI) (pp. 2951–2958). bibtex: '@inproceedings{Ahmadi Fahandar_Hüllermeier_2018, title={Learning to Rank Based on Analogical Reasoning}, booktitle={Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI)}, author={Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke}, year={2018}, pages={2951–2958} }' chicago: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” In Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2951–58, 2018. ieee: M. Ahmadi Fahandar and E. Hüllermeier, “Learning to Rank Based on Analogical Reasoning,” in Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–2958. mla: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–58. short: 'M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–2958.' date_created: 2019-06-07T08:49:33Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' language: - iso: eng page: 2951-2958 publication: Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI) status: public title: Learning to Rank Based on Analogical Reasoning type: conference user_id: '49109' year: '2018' ... --- _id: '10148' author: - first_name: Adil full_name: El Mesaoudi-Paul, Adil last_name: El Mesaoudi-Paul - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Robert full_name: Busa-Fekete, Robert last_name: Busa-Fekete citation: ama: 'El Mesaoudi-Paul A, Hüllermeier E, Busa-Fekete R. Ranking Distributions based on Noisy Sorting. In: Proc. 35th Int. Conference on Machine Learning (ICML). Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn; 2018:3469-3477.' apa: El Mesaoudi-Paul, A., Hüllermeier, E., & Busa-Fekete, R. (2018). Ranking Distributions based on Noisy Sorting. Proc. 35th Int. Conference on Machine Learning (ICML), 3469–3477. bibtex: '@inproceedings{El Mesaoudi-Paul_Hüllermeier_Busa-Fekete_2018, series={Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn}, title={Ranking Distributions based on Noisy Sorting}, booktitle={Proc. 35th Int. Conference on Machine Learning (ICML)}, publisher={Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn}, author={El Mesaoudi-Paul, Adil and Hüllermeier, Eyke and Busa-Fekete, Robert}, year={2018}, pages={3469–3477}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn} }' chicago: El Mesaoudi-Paul, Adil, Eyke Hüllermeier, and Robert Busa-Fekete. “Ranking Distributions Based on Noisy Sorting.” In Proc. 35th Int. Conference on Machine Learning (ICML), 3469–77. Verlagsschriftenreihe Des Heinz Nixdorf Instituts, Paderborn. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018. ieee: A. El Mesaoudi-Paul, E. Hüllermeier, and R. Busa-Fekete, “Ranking Distributions based on Noisy Sorting,” in Proc. 35th Int. Conference on Machine Learning (ICML), 2018, pp. 3469–3477. mla: El Mesaoudi-Paul, Adil, et al. “Ranking Distributions Based on Noisy Sorting.” Proc. 35th Int. Conference on Machine Learning (ICML), Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018, pp. 3469–77. short: 'A. El Mesaoudi-Paul, E. Hüllermeier, R. Busa-Fekete, in: Proc. 35th Int. Conference on Machine Learning (ICML), Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018, pp. 3469–3477.' date_created: 2019-06-07T09:02:37Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' language: - iso: eng page: 3469-3477 publication: Proc. 35th Int. Conference on Machine Learning (ICML) publisher: Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn status: public title: Ranking Distributions based on Noisy Sorting type: conference user_id: '5786' year: '2018' ... --- _id: '10149' author: - first_name: M. full_name: Hesse, M. last_name: Hesse - first_name: J. full_name: Timmermann, J. last_name: Timmermann - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Ansgar full_name: Trächtler, Ansgar last_name: Trächtler citation: ama: 'Hesse M, Timmermann J, Hüllermeier E, Trächtler A. A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart. In: Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24. ; 2018:15-20.' apa: 'Hesse, M., Timmermann, J., Hüllermeier, E., & Trächtler, A. (2018). A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart. Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 15–20.' bibtex: '@inproceedings{Hesse_Timmermann_Hüllermeier_Trächtler_2018, title={A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart}, booktitle={Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24}, author={Hesse, M. and Timmermann, J. and Hüllermeier, Eyke and Trächtler, Ansgar}, year={2018}, pages={15–20} }' chicago: 'Hesse, M., J. Timmermann, Eyke Hüllermeier, and Ansgar Trächtler. “A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.” In Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 15–20, 2018.' ieee: 'M. Hesse, J. Timmermann, E. Hüllermeier, and A. Trächtler, “A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart,” in Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.' mla: 'Hesse, M., et al. “A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.” Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.' short: 'M. Hesse, J. Timmermann, E. Hüllermeier, A. Trächtler, in: Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 2018, pp. 15–20.' date_created: 2019-06-07T09:10:51Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' language: - iso: eng page: 15-20 publication: 'Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24' status: public title: A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart type: conference user_id: '5786' year: '2018' ... --- _id: '10152' author: - first_name: E.Loza full_name: Mencia, E.Loza last_name: Mencia - first_name: J. full_name: Fürnkranz, J. last_name: Fürnkranz - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: M. full_name: Rapp, M. last_name: Rapp citation: ama: 'Mencia EL, Fürnkranz J, Hüllermeier E, Rapp M. Learning interpretable rules for multi-label classification. In: Jair Escalante H, Escalera S, Guyon I, et al., eds. Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer; 2018:81-113.' apa: Mencia, E. L., Fürnkranz, J., Hüllermeier, E., & Rapp, M. (2018). Learning interpretable rules for multi-label classification. In H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, & M. A. J. van Gerven (Eds.), Explainable and Interpretable Models in Computer Vision and Machine Learning (pp. 81–113). Springer. bibtex: '@inbook{Mencia_Fürnkranz_Hüllermeier_Rapp_2018, series={The Springer Series on Challenges in Machine Learning}, title={Learning interpretable rules for multi-label classification}, booktitle={Explainable and Interpretable Models in Computer Vision and Machine Learning}, publisher={Springer}, author={Mencia, E.Loza and Fürnkranz, J. and Hüllermeier, Eyke and Rapp, M.}, editor={Jair Escalante, H. and Escalera, S. and Guyon, I. and Baro, X. and Güclüütürk, Y. and Güclü, U. and van Gerven, M.A.J.Editors}, year={2018}, pages={81–113}, collection={The Springer Series on Challenges in Machine Learning} }' chicago: Mencia, E.Loza, J. Fürnkranz, Eyke Hüllermeier, and M. Rapp. “Learning Interpretable Rules for Multi-Label Classification.” In Explainable and Interpretable Models in Computer Vision and Machine Learning, edited by H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M.A.J. van Gerven, 81–113. The Springer Series on Challenges in Machine Learning. Springer, 2018. ieee: E. L. Mencia, J. Fürnkranz, E. Hüllermeier, and M. Rapp, “Learning interpretable rules for multi-label classification,” in Explainable and Interpretable Models in Computer Vision and Machine Learning, H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M. A. J. van Gerven, Eds. Springer, 2018, pp. 81–113. mla: Mencia, E. Loz., et al. “Learning Interpretable Rules for Multi-Label Classification.” Explainable and Interpretable Models in Computer Vision and Machine Learning, edited by H. Jair Escalante et al., Springer, 2018, pp. 81–113. short: 'E.L. Mencia, J. Fürnkranz, E. Hüllermeier, M. Rapp, in: H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, M.A.J. van Gerven (Eds.), Explainable and Interpretable Models in Computer Vision and Machine Learning, Springer, 2018, pp. 81–113.' date_created: 2019-06-07T09:17:56Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' editor: - first_name: H. full_name: Jair Escalante, H. last_name: Jair Escalante - first_name: S. full_name: Escalera, S. last_name: Escalera - first_name: I. full_name: Guyon, I. last_name: Guyon - first_name: X. full_name: Baro, X. last_name: Baro - first_name: Y. full_name: Güclüütürk, Y. last_name: Güclüütürk - first_name: U. full_name: Güclü, U. last_name: Güclü - first_name: M.A.J. full_name: van Gerven, M.A.J. last_name: van Gerven language: - iso: eng page: 81-113 publication: Explainable and Interpretable Models in Computer Vision and Machine Learning publisher: Springer series_title: The Springer Series on Challenges in Machine Learning status: public title: Learning interpretable rules for multi-label classification type: book_chapter user_id: '49109' year: '2018' ... --- _id: '10181' author: - first_name: Vu-Linh full_name: Nguyen, Vu-Linh last_name: Nguyen - first_name: Sebastian full_name: Destercke, Sebastian last_name: Destercke - first_name: M.-H. full_name: Masson, M.-H. last_name: Masson - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Nguyen V-L, Destercke S, Masson M-H, Hüllermeier E. Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. In: Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI). ; 2018:5089-5095.' apa: Nguyen, V.-L., Destercke, S., Masson, M.-H., & Hüllermeier, E. (2018). Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 5089–5095. bibtex: '@inproceedings{Nguyen_Destercke_Masson_Hüllermeier_2018, title={Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty}, booktitle={Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI)}, author={Nguyen, Vu-Linh and Destercke, Sebastian and Masson, M.-H. and Hüllermeier, Eyke}, year={2018}, pages={5089–5095} }' chicago: Nguyen, Vu-Linh, Sebastian Destercke, M.-H. Masson, and Eyke Hüllermeier. “Reliable Multi-Class Classification Based on Pairwise Epistemic and Aleatoric Uncertainty.” In Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 5089–95, 2018. ieee: V.-L. Nguyen, S. Destercke, M.-H. Masson, and E. Hüllermeier, “Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty,” in Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095. mla: Nguyen, Vu-Linh, et al. “Reliable Multi-Class Classification Based on Pairwise Epistemic and Aleatoric Uncertainty.” Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–95. short: 'V.-L. Nguyen, S. Destercke, M.-H. Masson, E. Hüllermeier, in: Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.' date_created: 2019-06-07T12:31:20Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' language: - iso: eng page: 5089-5095 publication: Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI) status: public title: Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty type: conference user_id: '5786' year: '2018' ... --- _id: '10184' author: - first_name: Dirk full_name: Schäfer, Dirk last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Proc. 21st Int. Conference on Discovery Science (DS). ; 2018:161-175.' apa: Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement Learning Using Dyad Ranking. Proc. 21st Int. Conference on Discovery Science (DS), 161–175. bibtex: '@inproceedings{Schäfer_Hüllermeier_2018, title={Preference-Based Reinforcement Learning Using Dyad Ranking}, booktitle={Proc. 21st Int. Conference on Discovery Science (DS)}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={161–175} }' chicago: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” In Proc. 21st Int. Conference on Discovery Science (DS), 161–75, 2018. ieee: D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using Dyad Ranking,” in Proc. 21st Int. Conference on Discovery Science (DS), 2018, pp. 161–175. mla: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” Proc. 21st Int. Conference on Discovery Science (DS), 2018, pp. 161–75. short: 'D. Schäfer, E. Hüllermeier, in: Proc. 21st Int. Conference on Discovery Science (DS), 2018, pp. 161–175.' date_created: 2019-06-07T12:33:58Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' language: - iso: eng page: 161-175 publication: Proc. 21st Int. Conference on Discovery Science (DS) status: public title: Preference-Based Reinforcement Learning Using Dyad Ranking type: conference user_id: '5786' year: '2018' ... --- _id: '10276' author: - first_name: Dirk full_name: Schäfer, Dirk last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: Schäfer D, Hüllermeier E. Dyad Ranking Using Plackett-Luce Models based on joint feature representations. Machine Learning. 2018;107(5):903-941. apa: Schäfer, D., & Hüllermeier, E. (2018). Dyad Ranking Using Plackett-Luce Models based on joint feature representations. Machine Learning, 107(5), 903–941. bibtex: '@article{Schäfer_Hüllermeier_2018, title={Dyad Ranking Using Plackett-Luce Models based on joint feature representations}, volume={107}, number={5}, journal={Machine Learning}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2018}, pages={903–941} }' chicago: 'Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning 107, no. 5 (2018): 903–41.' ieee: D. Schäfer and E. Hüllermeier, “Dyad Ranking Using Plackett-Luce Models based on joint feature representations,” Machine Learning, vol. 107, no. 5, pp. 903–941, 2018. mla: Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning, vol. 107, no. 5, 2018, pp. 903–41. short: D. Schäfer, E. Hüllermeier, Machine Learning 107 (2018) 903–941. date_created: 2019-06-19T14:58:10Z date_updated: 2022-01-06T06:50:33Z department: - _id: '34' - _id: '7' - _id: '355' - _id: '26' intvolume: ' 107' issue: '5' language: - iso: eng page: 903-941 publication: Machine Learning status: public title: Dyad Ranking Using Plackett-Luce Models based on joint feature representations type: journal_article user_id: '49109' volume: 107 year: '2018' ... --- _id: '1379' author: - first_name: Nina full_name: Seemann, Nina id: '65408' last_name: Seemann - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 - first_name: Marie-Luis full_name: Merten, Marie-Luis last_name: Merten - first_name: Doris full_name: Tophinke, Doris id: '16277' last_name: Tophinke - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Seemann N, Geierhos M, Merten M-L, Tophinke D, Wever MD, Hüllermeier E. Supporting the Cognitive Process in Annotation Tasks. In: Eckart K, Schlechtweg D, eds. Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft. ; 2018.' apa: Seemann, N., Geierhos, M., Merten, M.-L., Tophinke, D., Wever, M. D., & Hüllermeier, E. (2018). Supporting the Cognitive Process in Annotation Tasks. In K. Eckart & D. Schlechtweg (Eds.), Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft. bibtex: '@inproceedings{Seemann_Geierhos_Merten_Tophinke_Wever_Hüllermeier_2018, title={Supporting the Cognitive Process in Annotation Tasks}, booktitle={Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft}, author={Seemann, Nina and Geierhos, Michaela and Merten, Marie-Luis and Tophinke, Doris and Wever, Marcel Dominik and Hüllermeier, Eyke}, editor={Eckart, Kerstin and Schlechtweg, Dominik }, year={2018} }' chicago: Seemann, Nina, Michaela Geierhos, Marie-Luis Merten, Doris Tophinke, Marcel Dominik Wever, and Eyke Hüllermeier. “Supporting the Cognitive Process in Annotation Tasks.” In Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg, 2018. ieee: N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M. D. Wever, and E. Hüllermeier, “Supporting the Cognitive Process in Annotation Tasks,” in Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, Stuttgart, Germany, 2018. mla: Seemann, Nina, et al. “Supporting the Cognitive Process in Annotation Tasks.” Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg, 2018. short: 'N. Seemann, M. Geierhos, M.-L. Merten, D. Tophinke, M.D. Wever, E. Hüllermeier, in: K. Eckart, D. Schlechtweg (Eds.), Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, 2018.' conference: end_date: 2018-03-09 location: Stuttgart, Germany name: Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft start_date: 2018-03-07 date_created: 2018-03-19T15:23:25Z date_updated: 2023-01-09T14:56:56Z ddc: - '410' department: - _id: '36' - _id: '1' - _id: '579' - _id: '115' - _id: '355' - _id: '115' editor: - first_name: 'Kerstin ' full_name: 'Eckart, Kerstin ' last_name: Eckart - first_name: 'Dominik ' full_name: 'Schlechtweg, Dominik ' last_name: Schlechtweg file: - access_level: closed content_type: application/pdf creator: wever date_created: 2018-11-06T15:32:38Z date_updated: 2018-11-06T15:32:38Z file_id: '5389' file_name: 2018_dgfs-cl-poster-seemann-etal.pdf file_size: 158928 relation: main_file success: 1 file_date_updated: 2018-11-06T15:32:38Z has_accepted_license: '1' language: - iso: ger main_file_link: - open_access: '1' url: https://www.dgfs2018.uni-stuttgart.de/programm/postersession/programm-cl-postersession/2018_dgfs-cl-poster-seemann-etal.pdf oa: '1' project: - _id: '39' name: InterGramm publication: Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft publication_status: published quality_controlled: '1' status: public title: Supporting the Cognitive Process in Annotation Tasks type: conference_abstract user_id: '16277' year: '2018' ... --- _id: '24152' author: - first_name: Arunselvan full_name: Ramaswamy, Arunselvan id: '66937' last_name: Ramaswamy orcid: https://orcid.org/ 0000-0001-7547-8111 - first_name: Shalabh full_name: Bhatnagar, Shalabh last_name: Bhatnagar citation: ama: Ramaswamy A, Bhatnagar S. Analysis of gradient descent methods with nondiminishing bounded errors. IEEE Transactions on Automatic Control. 2017;63(5):1465-1471. apa: Ramaswamy, A., & Bhatnagar, S. (2017). Analysis of gradient descent methods with nondiminishing bounded errors. IEEE Transactions on Automatic Control, 63(5), 1465–1471. bibtex: '@article{Ramaswamy_Bhatnagar_2017, title={Analysis of gradient descent methods with nondiminishing bounded errors}, volume={63}, number={5}, journal={IEEE Transactions on Automatic Control}, publisher={IEEE}, author={Ramaswamy, Arunselvan and Bhatnagar, Shalabh}, year={2017}, pages={1465–1471} }' chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic Control 63, no. 5 (2017): 1465–71.' ieee: A. Ramaswamy and S. Bhatnagar, “Analysis of gradient descent methods with nondiminishing bounded errors,” IEEE Transactions on Automatic Control, vol. 63, no. 5, pp. 1465–1471, 2017. mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic Control, vol. 63, no. 5, IEEE, 2017, pp. 1465–71. short: A. Ramaswamy, S. Bhatnagar, IEEE Transactions on Automatic Control 63 (2017) 1465–1471. date_created: 2021-09-10T10:19:40Z date_updated: 2022-01-06T06:56:08Z department: - _id: '355' extern: '1' intvolume: ' 63' issue: '5' language: - iso: eng page: 1465-1471 publication: IEEE Transactions on Automatic Control publisher: IEEE status: public title: Analysis of gradient descent methods with nondiminishing bounded errors type: journal_article user_id: '66937' volume: 63 year: '2017' ... --- _id: '24153' author: - first_name: Arunselvan full_name: Ramaswamy, Arunselvan id: '66937' last_name: Ramaswamy orcid: https://orcid.org/ 0000-0001-7547-8111 - first_name: Shalabh full_name: Bhatnagar, Shalabh last_name: Bhatnagar citation: ama: Ramaswamy A, Bhatnagar S. A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions. Mathematics of Operations Research. 2017;42(3):648-661. apa: Ramaswamy, A., & Bhatnagar, S. (2017). A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions. Mathematics of Operations Research, 42(3), 648–661. bibtex: '@article{Ramaswamy_Bhatnagar_2017, title={A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions}, volume={42}, number={3}, journal={Mathematics of Operations Research}, publisher={INFORMS}, author={Ramaswamy, Arunselvan and Bhatnagar, Shalabh}, year={2017}, pages={648–661} }' chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions.” Mathematics of Operations Research 42, no. 3 (2017): 648–61.' ieee: A. Ramaswamy and S. Bhatnagar, “A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions,” Mathematics of Operations Research, vol. 42, no. 3, pp. 648–661, 2017. mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions.” Mathematics of Operations Research, vol. 42, no. 3, INFORMS, 2017, pp. 648–61. short: A. Ramaswamy, S. Bhatnagar, Mathematics of Operations Research 42 (2017) 648–661. date_created: 2021-09-10T10:21:02Z date_updated: 2022-01-06T06:56:08Z department: - _id: '355' extern: '1' intvolume: ' 42' issue: '3' language: - iso: eng page: 648-661 publication: Mathematics of Operations Research publisher: INFORMS status: public title: A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions type: journal_article user_id: '66937' volume: 42 year: '2017' ... --- _id: '3325' author: - first_name: Vitalik full_name: Melnikov, Vitalik last_name: Melnikov - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing; 2017. doi:10.5445/KSP/1000074341' apa: 'Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing. https://doi.org/10.5445/KSP/1000074341' bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics}, DOI={10.5445/KSP/1000074341}, booktitle={Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017}, publisher={KIT Scientific Publishing}, author={Melnikov, Vitalik and Hüllermeier, Eyke}, year={2017} }' chicago: 'Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” In Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing, 2017. https://doi.org/10.5445/KSP/1000074341.' ieee: 'V. Melnikov and E. Hüllermeier, “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics,” in Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, 2017.' mla: 'Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017, doi:10.5445/KSP/1000074341.' short: 'V. Melnikov, E. Hüllermeier, in: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017.' date_created: 2018-06-25T08:14:49Z date_updated: 2022-01-06T06:59:10Z ddc: - '000' department: - _id: '355' doi: 10.5445/KSP/1000074341 file: - access_level: closed content_type: application/pdf creator: melnikov date_created: 2018-11-30T09:47:59Z date_updated: 2018-11-30T09:47:59Z file_id: '5987' file_name: main.pdf file_size: 1829552 relation: main_file success: 1 file_date_updated: 2018-11-30T09:47:59Z has_accepted_license: '1' language: - iso: eng project: - _id: '11' name: SFB 901 - Subproject B3 - _id: '3' name: SFB 901 - Project Area B - _id: '1' name: SFB 901 publication: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017 publisher: KIT Scientific Publishing status: public title: 'Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics' type: conference user_id: '15504' year: '2017' ... --- _id: '115' abstract: - lang: eng text: 'Whenever customers have to decide between different instances of the same product, they are interested in buying the best product. In contrast, companies are interested in reducing the construction effort (and usually as a consequence thereof, the quality) to gain profit. The described setting is widely known as opposed preferences in quality of the product and also applies to the context of service-oriented computing. In general, service-oriented computing emphasizes the construction of large software systems out of existing services, where services are small and self-contained pieces of software that adhere to a specified interface. Several implementations of the same interface are considered as several instances of the same service. Thereby, customers are interested in buying the best service implementation for their service composition wrt. to metrics, such as costs, energy, memory consumption, or execution time. One way to ensure the service quality is to employ certificates, which can come in different kinds: Technical certificates proving correctness can be automatically constructed by the service provider and again be automatically checked by the user. Digital certificates allow proof of the integrity of a product. Other certificates might be rolled out if service providers follow a good software construction principle, which is checked in annual audits. Whereas all of these certificates are handled differently in service markets, what they have in common is that they influence the buying decisions of customers. In this paper, we review state-of-the-art developments in certification with respect to service-oriented computing. We not only discuss how certificates are constructed and handled in service-oriented computing but also review the effects of certificates on the market from an economic perspective.' author: - first_name: Marie-Christine full_name: Jakobs, Marie-Christine last_name: Jakobs - first_name: Julia full_name: Krämer, Julia last_name: Krämer - first_name: Dirk full_name: van Straaten, Dirk id: '10311' last_name: van Straaten - first_name: Theodor full_name: Lettmann, Theodor id: '315' last_name: Lettmann orcid: 0000-0001-5859-2457 citation: ama: 'Jakobs M-C, Krämer J, van Straaten D, Lettmann T. Certification Matters for Service Markets. In: Marcelo De Barros, Janusz Klink,Tadeus Uhl TP, ed. The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION). ; 2017:7-12.' apa: Jakobs, M.-C., Krämer, J., van Straaten, D., & Lettmann, T. (2017). Certification Matters for Service Markets. In T. P. Marcelo De Barros, Janusz Klink,Tadeus Uhl (Ed.), The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION) (pp. 7–12). bibtex: '@inproceedings{Jakobs_Krämer_van Straaten_Lettmann_2017, title={Certification Matters for Service Markets}, booktitle={The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)}, author={Jakobs, Marie-Christine and Krämer, Julia and van Straaten, Dirk and Lettmann, Theodor}, editor={Marcelo De Barros, Janusz Klink,Tadeus Uhl, Thomas PrinzEditor}, year={2017}, pages={7–12} }' chicago: Jakobs, Marie-Christine, Julia Krämer, Dirk van Straaten, and Theodor Lettmann. “Certification Matters for Service Markets.” In The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus Uhl, 7–12, 2017. ieee: M.-C. Jakobs, J. Krämer, D. van Straaten, and T. Lettmann, “Certification Matters for Service Markets,” in The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), 2017, pp. 7–12. mla: Jakobs, Marie-Christine, et al. “Certification Matters for Service Markets.” The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus Uhl, 2017, pp. 7–12. short: 'M.-C. Jakobs, J. Krämer, D. van Straaten, T. Lettmann, in: T.P. Marcelo De Barros, Janusz Klink,Tadeus Uhl (Ed.), The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), 2017, pp. 7–12.' date_created: 2017-10-17T12:41:14Z date_updated: 2022-01-06T06:51:02Z ddc: - '040' department: - _id: '77' - _id: '355' - _id: '179' editor: - first_name: Thomas Prinz full_name: Marcelo De Barros, Janusz Klink,Tadeus Uhl, Thomas Prinz last_name: Marcelo De Barros, Janusz Klink,Tadeus Uhl file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-21T13:04:12Z date_updated: 2018-03-21T13:04:12Z file_id: '1564' file_name: 115-JakobsKraemerVanStraatenLettmann2017.pdf file_size: 133531 relation: main_file success: 1 file_date_updated: 2018-03-21T13:04:12Z has_accepted_license: '1' language: - iso: eng page: 7-12 project: - _id: '1' name: SFB 901 - _id: '10' name: SFB 901 - Subprojekt B2 - _id: '11' name: SFB 901 - Subproject B3 - _id: '12' name: SFB 901 - Subproject B4 - _id: '8' name: SFB 901 - Subproject A4 - _id: '2' name: SFB 901 - Project Area A - _id: '3' name: SFB 901 - Project Area B publication: The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION) status: public title: Certification Matters for Service Markets type: conference user_id: '477' year: '2017' ... --- _id: '1158' abstract: - lang: eng text: In this paper, we present the annotation challenges we have encountered when working on a historical language that was undergoing elaboration processes. We especially focus on syntactic ambiguity and gradience in Middle Low German, which causes uncertainty to some extent. Since current annotation tools consider construction contexts and the dynamics of the grammaticalization only partially, we plan to extend CorA – a web-based annotation tool for historical and other non-standard language data – to capture elaboration phenomena and annotator unsureness. Moreover, we seek to interactively learn morphological as well as syntactic annotations. author: - first_name: Nina full_name: Seemann, Nina id: '65408' last_name: Seemann - first_name: Marie-Luis full_name: Merten, Marie-Luis last_name: Merten - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 - first_name: Doris full_name: Tophinke, Doris last_name: Tophinke - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier citation: ama: 'Seemann N, Merten M-L, Geierhos M, Tophinke D, Hüllermeier E. Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German. In: Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL); 2017:40-45. doi:10.18653/v1/W17-2206' apa: 'Seemann, N., Merten, M.-L., Geierhos, M., Tophinke, D., & Hüllermeier, E. (2017). Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German. In Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (pp. 40–45). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/W17-2206' bibtex: '@inproceedings{Seemann_Merten_Geierhos_Tophinke_Hüllermeier_2017, place={Stroudsburg, PA, USA}, title={Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German}, DOI={10.18653/v1/W17-2206}, booktitle={Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature}, publisher={Association for Computational Linguistics (ACL)}, author={Seemann, Nina and Merten, Marie-Luis and Geierhos, Michaela and Tophinke, Doris and Hüllermeier, Eyke}, year={2017}, pages={40–45} }' chicago: 'Seemann, Nina, Marie-Luis Merten, Michaela Geierhos, Doris Tophinke, and Eyke Hüllermeier. “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German.” In Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, 40–45. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL), 2017. https://doi.org/10.18653/v1/W17-2206.' ieee: N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, and E. Hüllermeier, “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German,” in Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Vancouver, BC, Canada, 2017, pp. 40–45. mla: Seemann, Nina, et al. “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German.” Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Association for Computational Linguistics (ACL), 2017, pp. 40–45, doi:10.18653/v1/W17-2206. short: 'N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, E. Hüllermeier, in: Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Association for Computational Linguistics (ACL), Stroudsburg, PA, USA, 2017, pp. 40–45.' conference: end_date: 2017-08-04 location: Vancouver, BC, Canada name: Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2017) start_date: 2017-07-31 date_created: 2018-01-31T15:32:33Z date_updated: 2022-01-06T06:51:03Z department: - _id: '36' - _id: '579' - _id: '115' - _id: '355' - _id: '615' doi: 10.18653/v1/W17-2206 language: - iso: eng page: 40-45 place: Stroudsburg, PA, USA project: - _id: '39' name: InterGramm publication: Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature publication_status: published publisher: Association for Computational Linguistics (ACL) quality_controlled: '1' status: public title: Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German type: conference user_id: '13929' year: '2017' ... --- _id: '5694' author: - first_name: Nino Noel full_name: Schnitker, Nino Noel last_name: Schnitker citation: ama: Schnitker NN. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn; 2017. apa: Schnitker, N. N. (2017). Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn. bibtex: '@book{Schnitker_2017, title={Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies}, publisher={Universität Paderborn}, author={Schnitker, Nino Noel}, year={2017} }' chicago: Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn, 2017. ieee: N. N. Schnitker, Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn, 2017. mla: Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn, 2017. short: N.N. Schnitker, Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies, Universität Paderborn, 2017. date_created: 2018-11-15T08:10:48Z date_updated: 2022-01-06T07:02:35Z department: - _id: '355' language: - iso: ger project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publisher: Universität Paderborn status: public supervisor: - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier title: Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies type: bachelorsthesis user_id: '477' year: '2017' ... --- _id: '5722' author: - first_name: Pritha full_name: Gupta, Pritha last_name: Gupta - first_name: Alexander full_name: Hetzer, Alexander id: '38209' last_name: Hetzer - first_name: Tanja full_name: Tornede, Tanja last_name: Tornede - first_name: Sebastian full_name: Gottschalk, Sebastian last_name: Gottschalk - first_name: Andreas full_name: Kornelsen, Andreas last_name: Kornelsen - first_name: Sebastian full_name: Osterbrink, Sebastian last_name: Osterbrink - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier citation: ama: 'Gupta P, Hetzer A, Tornede T, et al. jPL: A Java-based Software Framework for Preference Learning. In: ; 2017.' apa: 'Gupta, P., Hetzer, A., Tornede, T., Gottschalk, S., Kornelsen, A., Osterbrink, S., … Hüllermeier, E. (2017). jPL: A Java-based Software Framework for Preference Learning. Presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock.' bibtex: '@inproceedings{Gupta_Hetzer_Tornede_Gottschalk_Kornelsen_Osterbrink_Pfannschmidt_Hüllermeier_2017, title={jPL: A Java-based Software Framework for Preference Learning}, author={Gupta, Pritha and Hetzer, Alexander and Tornede, Tanja and Gottschalk, Sebastian and Kornelsen, Andreas and Osterbrink, Sebastian and Pfannschmidt, Karlson and Hüllermeier, Eyke}, year={2017} }' chicago: 'Gupta, Pritha, Alexander Hetzer, Tanja Tornede, Sebastian Gottschalk, Andreas Kornelsen, Sebastian Osterbrink, Karlson Pfannschmidt, and Eyke Hüllermeier. “JPL: A Java-Based Software Framework for Preference Learning,” 2017.' ieee: 'P. Gupta et al., “jPL: A Java-based Software Framework for Preference Learning,” presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock, 2017.' mla: 'Gupta, Pritha, et al. JPL: A Java-Based Software Framework for Preference Learning. 2017.' short: 'P. Gupta, A. Hetzer, T. Tornede, S. Gottschalk, A. Kornelsen, S. Osterbrink, K. Pfannschmidt, E. Hüllermeier, in: 2017.' conference: end_date: 13.09.2017 location: Rostock name: 'WDA 2017 Workshops: KDML, FGWM, IR, and FGDB' start_date: 11.09.2017 date_created: 2018-11-19T07:32:31Z date_updated: 2022-01-06T07:02:37Z department: - _id: '355' extern: '1' language: - iso: eng status: public title: 'jPL: A Java-based Software Framework for Preference Learning' type: conference_abstract user_id: '38209' year: '2017' ... --- _id: '5724' author: - first_name: Alexander full_name: Hetzer, Alexander id: '38209' last_name: Hetzer - first_name: Tanja full_name: Tornede, Tanja last_name: Tornede citation: ama: Hetzer A, Tornede T. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. Universität Paderborn; 2017. apa: Hetzer, A., & Tornede, T. (2017). Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction. Universität Paderborn. bibtex: '@book{Hetzer_Tornede_2017, title={Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction}, publisher={Universität Paderborn}, author={Hetzer, Alexander and Tornede, Tanja}, year={2017} }' chicago: Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. Universität Paderborn, 2017. ieee: A. Hetzer and T. Tornede, Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction. Universität Paderborn, 2017. mla: Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. Universität Paderborn, 2017. short: A. Hetzer, T. Tornede, Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction, Universität Paderborn, 2017. date_created: 2018-11-19T07:49:13Z date_updated: 2022-01-06T07:02:37Z department: - _id: '355' - _id: '199' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publisher: Universität Paderborn status: public supervisor: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Kevin full_name: Tierney, Kevin last_name: Tierney title: Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction type: mastersthesis user_id: '477' year: '2017' ... --- _id: '71' abstract: - lang: eng text: Today, software verification tools have reached the maturity to be used for large scale programs. Different tools perform differently well on varying code. A software developer is hence faced with the problem of choosing a tool appropriate for her program at hand. A ranking of tools on programs could facilitate the choice. Such rankings can, however, so far only be obtained by running all considered tools on the program.In this paper, we present a machine learning approach to predicting rankings of tools on programs. The method builds upon so-called label ranking algorithms, which we complement with appropriate kernels providing a similarity measure for programs. Our kernels employ a graph representation for software source code that mixes elements of control flow and program dependence graphs with abstract syntax trees. Using data sets from the software verification competition SV-COMP, we demonstrate our rank prediction technique to generalize well and achieve a rather high predictive accuracy (rank correlation > 0.6). author: - first_name: Mike full_name: Czech, Mike last_name: Czech - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Marie-Christine full_name: Jakobs, Marie-Christine last_name: Jakobs - first_name: Heike full_name: Wehrheim, Heike id: '573' last_name: Wehrheim citation: ama: 'Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software Verification Tools. In: Proceedings of the 3rd International Workshop on Software Analytics. SWAN’17. ; 2017:23-26. doi:10.1145/3121257.3121262' apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting Rankings of Software Verification Tools. In Proceedings of the 3rd International Workshop on Software Analytics (pp. 23–26). https://doi.org/10.1145/3121257.3121262 bibtex: '@inproceedings{Czech_Hüllermeier_Jakobs_Wehrheim_2017, series={SWAN’17}, title={Predicting Rankings of Software Verification Tools}, DOI={10.1145/3121257.3121262}, booktitle={Proceedings of the 3rd International Workshop on Software Analytics}, author={Czech, Mike and Hüllermeier, Eyke and Jakobs, Marie-Christine and Wehrheim, Heike}, year={2017}, pages={23–26}, collection={SWAN’17} }' chicago: Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim. “Predicting Rankings of Software Verification Tools.” In Proceedings of the 3rd International Workshop on Software Analytics, 23–26. SWAN’17, 2017. https://doi.org/10.1145/3121257.3121262. ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, “Predicting Rankings of Software Verification Tools,” in Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26. mla: Czech, Mike, et al. “Predicting Rankings of Software Verification Tools.” Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26, doi:10.1145/3121257.3121262. short: 'M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26.' date_created: 2017-10-17T12:41:05Z date_updated: 2022-01-06T07:03:28Z ddc: - '000' department: - _id: '355' - _id: '77' doi: 10.1145/3121257.3121262 file: - access_level: closed content_type: application/pdf creator: ups date_created: 2018-11-02T14:24:29Z date_updated: 2018-11-02T14:24:29Z file_id: '5271' file_name: fsews17swan-swanmain1.pdf file_size: 822383 relation: main_file success: 1 file_date_updated: 2018-11-02T14:24:29Z has_accepted_license: '1' language: - iso: eng page: 23-26 project: - _id: '1' name: SFB 901 - _id: '12' name: SFB 901 - Subprojekt B4 - _id: '10' name: SFB 901 - Subproject B2 - _id: '3' name: SFB 901 - Project Area B - _id: '11' name: SFB 901 - Subproject B3 publication: Proceedings of the 3rd International Workshop on Software Analytics series_title: SWAN'17 status: public title: Predicting Rankings of Software Verification Tools type: conference user_id: '15504' year: '2017' ... --- _id: '72' abstract: - lang: eng text: 'Software verification competitions, such as the annual SV-COMP, evaluate software verification tools with respect to their effectivity and efficiency. Typically, the outcome of a competition is a (possibly category-specific) ranking of the tools. For many applications, such as building portfolio solvers, it would be desirable to have an idea of the (relative) performance of verification tools on a given verification task beforehand, i.e., prior to actually running all tools on the task.In this paper, we present a machine learning approach to predicting rankings of tools on verification tasks. The method builds upon so-called label ranking algorithms, which we complement with appropriate kernels providing a similarity measure for verification tasks. Our kernels employ a graph representation for software source code that mixes elements of control flow and program dependence graphs with abstract syntax trees. Using data sets from SV-COMP, we demonstrate our rank prediction technique to generalize well and achieve a rather high predictive accuracy. In particular, our method outperforms a recently proposed feature-based approach of Demyanova et al. (when applied to rank predictions). ' author: - first_name: Mike full_name: Czech, Mike last_name: Czech - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Marie-Christine full_name: Jakobs, Marie-Christine last_name: Jakobs - first_name: Heike full_name: Wehrheim, Heike id: '573' last_name: Wehrheim citation: ama: Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software Verification Competitions.; 2017. apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting Rankings of Software Verification Competitions. bibtex: '@book{Czech_Hüllermeier_Jakobs_Wehrheim_2017, title={Predicting Rankings of Software Verification Competitions}, author={Czech, Mike and Hüllermeier, Eyke and Jakobs, Marie-Christine and Wehrheim, Heike}, year={2017} }' chicago: Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim. Predicting Rankings of Software Verification Competitions, 2017. ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, Predicting Rankings of Software Verification Competitions. 2017. mla: Czech, Mike, et al. Predicting Rankings of Software Verification Competitions. 2017. short: M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Predicting Rankings of Software Verification Competitions, 2017. date_created: 2017-10-17T12:41:05Z date_updated: 2022-01-06T07:03:29Z ddc: - '000' department: - _id: '77' - _id: '355' file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-11-21T10:50:11Z date_updated: 2018-11-21T10:50:11Z file_id: '5782' file_name: "Predicting Rankings of So\x81ware Verification Competitions.pdf" file_size: 869984 relation: main_file success: 1 file_date_updated: 2018-11-21T10:50:11Z has_accepted_license: '1' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '11' name: SFB 901 - Subprojekt B3 - _id: '12' name: SFB 901 - Subprojekt B4 - _id: '3' name: SFB 901 - Project Area B status: public title: Predicting Rankings of Software Verification Competitions type: report user_id: '15504' year: '2017' ... --- _id: '10589' author: - first_name: J. full_name: Fürnkranz, J. last_name: Fürnkranz - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Encyclopedia of Machine Learning and Data Mining. ; 2017:1000-1005.' apa: Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In Encyclopedia of Machine Learning and Data Mining (pp. 1000–1005). bibtex: '@inbook{Fürnkranz_Hüllermeier_2017, title={Preference Learning}, booktitle={Encyclopedia of Machine Learning and Data Mining}, author={Fürnkranz, J. and Hüllermeier, Eyke}, year={2017}, pages={1000–1005} }' chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, 1000–1005, 2017. ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–1005. mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–05. short: 'J. Fürnkranz, E. Hüllermeier, in: Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–1005.' date_created: 2019-07-09T15:37:09Z date_updated: 2022-01-06T06:50:45Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 1000-1005 publication: Encyclopedia of Machine Learning and Data Mining status: public title: Preference Learning type: encyclopedia_article user_id: '49109' year: '2017' ... --- _id: '10784' author: - first_name: J. full_name: Fürnkranz, J. last_name: Fürnkranz - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. Encyclopedia of Machine Learning and Data Mining. Vol 107. Springer; 2017:1000-1005.' apa: Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining (Vol. 107, pp. 1000–1005). Springer. bibtex: '@inbook{Fürnkranz_Hüllermeier_2017, title={Preference Learning}, volume={107}, booktitle={Encyclopedia of Machine Learning and Data Mining}, publisher={Springer}, author={Fürnkranz, J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors}, year={2017}, pages={1000–1005} }' chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, 107:1000–1005. Springer, 2017. ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia of Machine Learning and Data Mining, vol. 107, C. Sammut and G. I. Webb, Eds. Springer, 2017, pp. 1000–1005. mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, vol. 107, Springer, 2017, pp. 1000–05. short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2017, pp. 1000–1005.' date_created: 2019-07-10T15:44:32Z date_updated: 2022-01-06T06:50:50Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: C. full_name: Sammut, C. last_name: Sammut - first_name: G.I. full_name: Webb, G.I. last_name: Webb intvolume: ' 107' language: - iso: eng page: 1000-1005 publication: Encyclopedia of Machine Learning and Data Mining publisher: Springer status: public title: Preference Learning type: book_chapter user_id: '49109' volume: 107 year: '2017' ... --- _id: '1180' abstract: - lang: eng text: These days, there is a strong rise in the needs for machine learning applications, requiring an automation of machine learning engineering which is referred to as AutoML. In AutoML the selection, composition and parametrization of machine learning algorithms is automated and tailored to a specific problem, resulting in a machine learning pipeline. Current approaches reduce the AutoML problem to optimization of hyperparameters. Based on recursive task networks, in this paper we present one approach from the field of automated planning and one evolutionary optimization approach. Instead of simply parametrizing a given pipeline, this allows for structure optimization of machine learning pipelines, as well. We evaluate the two approaches in an extensive evaluation, finding both approaches to have their strengths in different areas. Moreover, the two approaches outperform the state-of-the-art tool Auto-WEKA in many settings. author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization. In: 27th Workshop Computational Intelligence. Dortmund; 2017.' apa: 'Wever, M. D., Mohr, F., & Hüllermeier, E. (2017). Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization. In 27th Workshop Computational Intelligence. Dortmund.' bibtex: '@inproceedings{Wever_Mohr_Hüllermeier_2017, place={Dortmund}, title={Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization}, booktitle={27th Workshop Computational Intelligence}, author={Wever, Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2017} }' chicago: 'Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization.” In 27th Workshop Computational Intelligence. Dortmund, 2017.' ieee: 'M. D. Wever, F. Mohr, and E. Hüllermeier, “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization,” in 27th Workshop Computational Intelligence, Dortmund, 2017.' mla: 'Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization.” 27th Workshop Computational Intelligence, 2017.' short: 'M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence, Dortmund, 2017.' conference: end_date: 2017-11-24 location: Dortmund name: 27th Workshop Computational Intelligence start_date: 2017-11-23 date_created: 2018-02-22T07:19:18Z date_updated: 2022-01-06T06:51:09Z ddc: - '000' department: - _id: '355' file: - access_level: closed content_type: application/pdf creator: wever date_created: 2018-11-06T15:28:09Z date_updated: 2018-11-06T15:28:09Z file_id: '5387' file_name: CI Workshop AutoML.pdf file_size: 323589 relation: main_file success: 1 file_date_updated: 2018-11-06T15:28:09Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://publikationen.bibliothek.kit.edu/1000074341/4643874 oa: '1' place: Dortmund project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 publication: 27th Workshop Computational Intelligence publication_status: published status: public title: 'Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization' type: conference user_id: '49109' year: '2017' ... --- _id: '15397' author: - first_name: Vitaly full_name: Melnikov, Vitaly last_name: Melnikov - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Melnikov V, Hüllermeier E. Optimizing the structure of nested dichotomies. A comparison of two heuristics. In: Hoffmann F, Hüllermeier E, Mikut R, eds. In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany. KIT Scientific Publishing; 2017:1-12.' apa: Melnikov, V., & Hüllermeier, E. (2017). Optimizing the structure of nested dichotomies. A comparison of two heuristics. In F. Hoffmann, E. Hüllermeier, & R. Mikut (Eds.), in Proceedings 27th Workshop Computational Intelligence, Dortmund Germany (pp. 1–12). KIT Scientific Publishing. bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the structure of nested dichotomies. A comparison of two heuristics}, booktitle={in Proceedings 27th Workshop Computational Intelligence, Dortmund Germany}, publisher={KIT Scientific Publishing}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, editor={Hoffmann, F. and Hüllermeier, Eyke and Mikut, R.Editors}, year={2017}, pages={1–12} }' chicago: Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies. A Comparison of Two Heuristics.” In In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann, Eyke Hüllermeier, and R. Mikut, 1–12. KIT Scientific Publishing, 2017. ieee: V. Melnikov and E. Hüllermeier, “Optimizing the structure of nested dichotomies. A comparison of two heuristics,” in in Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, 2017, pp. 1–12. mla: Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies. A Comparison of Two Heuristics.” In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann et al., KIT Scientific Publishing, 2017, pp. 1–12. short: 'V. Melnikov, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2017, pp. 1–12.' date_created: 2019-12-19T15:48:38Z date_updated: 2022-01-06T06:52:22Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: F. full_name: Hoffmann, F. last_name: Hoffmann - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: R. full_name: Mikut, R. last_name: Mikut language: - iso: eng page: 1-12 publication: in Proceedings 27th Workshop Computational Intelligence, Dortmund Germany publisher: KIT Scientific Publishing status: public title: Optimizing the structure of nested dichotomies. A comparison of two heuristics type: conference user_id: '49109' year: '2017' ... --- _id: '15399' author: - first_name: M. full_name: Czech, M. last_name: Czech - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: M.C. full_name: Jacobs, M.C. last_name: Jacobs - first_name: Heike full_name: Wehrheim, Heike last_name: Wehrheim citation: ama: 'Czech M, Hüllermeier E, Jacobs MC, Wehrheim H. Predicting rankings of software verification tools. In: In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany. ; 2017.' apa: Czech, M., Hüllermeier, E., Jacobs, M. C., & Wehrheim, H. (2017). Predicting rankings of software verification tools. In in Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany. bibtex: '@inproceedings{Czech_Hüllermeier_Jacobs_Wehrheim_2017, title={Predicting rankings of software verification tools}, booktitle={in Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany}, author={Czech, M. and Hüllermeier, Eyke and Jacobs, M.C. and Wehrheim, Heike}, year={2017} }' chicago: Czech, M., Eyke Hüllermeier, M.C. Jacobs, and Heike Wehrheim. “Predicting Rankings of Software Verification Tools.” In In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany, 2017. ieee: M. Czech, E. Hüllermeier, M. C. Jacobs, and H. Wehrheim, “Predicting rankings of software verification tools,” in in Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany, 2017. mla: Czech, M., et al. “Predicting Rankings of Software Verification Tools.” In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany, 2017. short: 'M. Czech, E. Hüllermeier, M.C. Jacobs, H. Wehrheim, in: In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany, 2017.' date_created: 2019-12-19T15:59:42Z date_updated: 2022-01-06T06:52:22Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng publication: in Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany status: public title: Predicting rankings of software verification tools type: conference user_id: '49109' year: '2017' ... --- _id: '15110' author: - first_name: Ines full_name: Couso, Ines last_name: Couso - first_name: D. full_name: Dubois, D. last_name: Dubois - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Couso I, Dubois D, Hüllermeier E. Maximum likelihood estimation and coarse data. In: In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain. Springer; 2017:3-16.' apa: Couso, I., Dubois, D., & Hüllermeier, E. (2017). Maximum likelihood estimation and coarse data. In in Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain (pp. 3–16). Springer. bibtex: '@inproceedings{Couso_Dubois_Hüllermeier_2017, title={Maximum likelihood estimation and coarse data}, booktitle={in Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain}, publisher={Springer}, author={Couso, Ines and Dubois, D. and Hüllermeier, Eyke}, year={2017}, pages={3–16} }' chicago: Couso, Ines, D. Dubois, and Eyke Hüllermeier. “Maximum Likelihood Estimation and Coarse Data.” In In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, 3–16. Springer, 2017. ieee: I. Couso, D. Dubois, and E. Hüllermeier, “Maximum likelihood estimation and coarse data,” in in Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, 2017, pp. 3–16. mla: Couso, Ines, et al. “Maximum Likelihood Estimation and Coarse Data.” In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, Springer, 2017, pp. 3–16. short: 'I. Couso, D. Dubois, E. Hüllermeier, in: In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, Springer, 2017, pp. 3–16.' date_created: 2019-11-21T16:38:39Z date_updated: 2022-01-06T06:52:15Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 3-16 publication: in Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain publisher: Springer status: public title: Maximum likelihood estimation and coarse data type: conference user_id: '49109' year: '2017' ... --- _id: '10204' author: - first_name: Ralph full_name: Ewerth, Ralph last_name: Ewerth - first_name: M. full_name: Springstein, M. last_name: Springstein - first_name: E. full_name: Müller, E. last_name: Müller - first_name: A. full_name: Balz, A. last_name: Balz - first_name: J. full_name: Gehlhaar, J. last_name: Gehlhaar - first_name: T. full_name: Naziyok, T. last_name: Naziyok - first_name: K. full_name: Dembczynski, K. last_name: Dembczynski - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Ewerth R, Springstein M, Müller E, et al. Estimating relative depth in single images via rankboost. In: Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017). ; 2017:919-924.' apa: Ewerth, R., Springstein, M., Müller, E., Balz, A., Gehlhaar, J., Naziyok, T., … Hüllermeier, E. (2017). Estimating relative depth in single images via rankboost. In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017) (pp. 919–924). bibtex: '@inproceedings{Ewerth_Springstein_Müller_Balz_Gehlhaar_Naziyok_Dembczynski_Hüllermeier_2017, title={Estimating relative depth in single images via rankboost}, booktitle={Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017)}, author={Ewerth, Ralph and Springstein, M. and Müller, E. and Balz, A. and Gehlhaar, J. and Naziyok, T. and Dembczynski, K. and Hüllermeier, Eyke}, year={2017}, pages={919–924} }' chicago: Ewerth, Ralph, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok, K. Dembczynski, and Eyke Hüllermeier. “Estimating Relative Depth in Single Images via Rankboost.” In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 919–24, 2017. ieee: R. Ewerth et al., “Estimating relative depth in single images via rankboost,” in Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp. 919–924. mla: Ewerth, Ralph, et al. “Estimating Relative Depth in Single Images via Rankboost.” Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp. 919–24. short: 'R. Ewerth, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok, K. Dembczynski, E. Hüllermeier, in: Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp. 919–924.' date_created: 2019-06-07T15:18:24Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 919-924 publication: Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017) status: public title: Estimating relative depth in single images via rankboost type: conference user_id: '49109' year: '2017' ... --- _id: '10205' author: - first_name: Mohsen full_name: Ahmadi Fahandar, Mohsen last_name: Ahmadi Fahandar - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Ines full_name: Couso, Ines last_name: Couso citation: ama: 'Ahmadi Fahandar M, Hüllermeier E, Couso I. Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening. In: Proc. 34th Int. Conf. on Machine Learning (ICML 2017). ; 2017:1078-1087.' apa: 'Ahmadi Fahandar, M., Hüllermeier, E., & Couso, I. (2017). Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening. In Proc. 34th Int. Conf. on Machine Learning (ICML 2017) (pp. 1078–1087).' bibtex: '@inproceedings{Ahmadi Fahandar_Hüllermeier_Couso_2017, title={Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening}, booktitle={Proc. 34th Int. Conf. on Machine Learning (ICML 2017)}, author={Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke and Couso, Ines}, year={2017}, pages={1078–1087} }' chicago: 'Ahmadi Fahandar, Mohsen, Eyke Hüllermeier, and Ines Couso. “Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening.” In Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 1078–87, 2017.' ieee: 'M. Ahmadi Fahandar, E. Hüllermeier, and I. Couso, “Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening,” in Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 2017, pp. 1078–1087.' mla: 'Ahmadi Fahandar, Mohsen, et al. “Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening.” Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 2017, pp. 1078–87.' short: 'M. Ahmadi Fahandar, E. Hüllermeier, I. Couso, in: Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 2017, pp. 1078–1087.' date_created: 2019-06-07T15:22:01Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 1078-1087 publication: Proc. 34th Int. Conf. on Machine Learning (ICML 2017) status: public title: 'Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening' type: conference user_id: '49109' year: '2017' ... --- _id: '10206' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Theodor full_name: Lettmann, Theodor id: '315' last_name: Lettmann orcid: 0000-0001-5859-2457 - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Mohr F, Lettmann T, Hüllermeier E. Planning with Independent Task Networks. In: Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017). ; 2017:193-206. doi:10.1007/978-3-319-67190-1_15' apa: Mohr, F., Lettmann, T., & Hüllermeier, E. (2017). Planning with Independent Task Networks. In Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017) (pp. 193–206). https://doi.org/10.1007/978-3-319-67190-1_15 bibtex: '@inproceedings{Mohr_Lettmann_Hüllermeier_2017, title={Planning with Independent Task Networks}, DOI={10.1007/978-3-319-67190-1_15}, booktitle={Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017)}, author={Mohr, Felix and Lettmann, Theodor and Hüllermeier, Eyke}, year={2017}, pages={193–206} }' chicago: Mohr, Felix, Theodor Lettmann, and Eyke Hüllermeier. “Planning with Independent Task Networks.” In Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 193–206, 2017. https://doi.org/10.1007/978-3-319-67190-1_15. ieee: F. Mohr, T. Lettmann, and E. Hüllermeier, “Planning with Independent Task Networks,” in Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206. mla: Mohr, Felix, et al. “Planning with Independent Task Networks.” Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206, doi:10.1007/978-3-319-67190-1_15. short: 'F. Mohr, T. Lettmann, E. Hüllermeier, in: Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206.' date_created: 2019-06-07T15:24:16Z date_updated: 2022-01-06T06:50:31Z ddc: - '000' department: - _id: '7' - _id: '34' - _id: '355' doi: 10.1007/978-3-319-67190-1_15 file: - access_level: open_access content_type: application/pdf creator: lettmann date_created: 2020-02-28T12:50:18Z date_updated: 2020-02-28T12:50:18Z file_id: '16157' file_name: ki17.pdf file_size: 374421 relation: main_file file_date_updated: 2020-02-28T12:50:18Z has_accepted_license: '1' language: - iso: eng oa: '1' page: 193-206 publication: Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017) status: public title: Planning with Independent Task Networks type: conference user_id: '315' year: '2017' ... --- _id: '10207' author: - first_name: M. full_name: Czech, M. last_name: Czech - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: M.-C. full_name: Jakobs, M.-C. last_name: Jakobs - first_name: Heike full_name: Wehrheim, Heike id: '573' last_name: Wehrheim citation: ama: 'Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting rankings of software verification tools. In: Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017. ; 2017:23-26.' apa: Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting rankings of software verification tools. In Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017 (pp. 23–26). bibtex: '@inproceedings{Czech_Hüllermeier_Jakobs_Wehrheim_2017, title={Predicting rankings of software verification tools}, booktitle={Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017}, author={Czech, M. and Hüllermeier, Eyke and Jakobs, M.-C. and Wehrheim, Heike}, year={2017}, pages={23–26} }' chicago: Czech, M., Eyke Hüllermeier, M.-C. Jakobs, and Heike Wehrheim. “Predicting Rankings of Software Verification Tools.” In Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 23–26, 2017. ieee: M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, “Predicting rankings of software verification tools,” in Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26. mla: Czech, M., et al. “Predicting Rankings of Software Verification Tools.” Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26. short: 'M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26.' date_created: 2019-06-07T15:27:47Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 23-26 publication: Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017 status: public title: Predicting rankings of software verification tools type: conference user_id: '49109' year: '2017' ... --- _id: '10208' author: - first_name: Ines full_name: Couso, Ines last_name: Couso - first_name: D. full_name: Dubois, D. last_name: Dubois - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Couso I, Dubois D, Hüllermeier E. Maximum Likelihood Estimation and Coarse Data. In: Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017). ; 2017:3-16.' apa: Couso, I., Dubois, D., & Hüllermeier, E. (2017). Maximum Likelihood Estimation and Coarse Data. In Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017) (pp. 3–16). bibtex: '@inproceedings{Couso_Dubois_Hüllermeier_2017, title={Maximum Likelihood Estimation and Coarse Data}, booktitle={Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017)}, author={Couso, Ines and Dubois, D. and Hüllermeier, Eyke}, year={2017}, pages={3–16} }' chicago: Couso, Ines, D. Dubois, and Eyke Hüllermeier. “Maximum Likelihood Estimation and Coarse Data.” In Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 3–16, 2017. ieee: I. Couso, D. Dubois, and E. Hüllermeier, “Maximum Likelihood Estimation and Coarse Data,” in Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 2017, pp. 3–16. mla: Couso, Ines, et al. “Maximum Likelihood Estimation and Coarse Data.” Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 2017, pp. 3–16. short: 'I. Couso, D. Dubois, E. Hüllermeier, in: Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 2017, pp. 3–16.' date_created: 2019-06-07T15:30:48Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 3-16 publication: Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017) status: public title: Maximum Likelihood Estimation and Coarse Data type: conference user_id: '49109' year: '2017' ... --- _id: '10209' author: - first_name: Mohsen full_name: Ahmadi Fahandar, Mohsen last_name: Ahmadi Fahandar - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Ahmadi Fahandar M, Hüllermeier E. Learning to Rank based on Analogical Reasoning. In: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence. ; 2017.' apa: Ahmadi Fahandar, M., & Hüllermeier, E. (2017). Learning to Rank based on Analogical Reasoning. In Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence. bibtex: '@inproceedings{Ahmadi Fahandar_Hüllermeier_2017, title={Learning to Rank based on Analogical Reasoning}, booktitle={Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence}, author={Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke}, year={2017} }' chicago: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” In Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017. ieee: M. Ahmadi Fahandar and E. Hüllermeier, “Learning to Rank based on Analogical Reasoning,” in Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017. mla: Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017. short: 'M. Ahmadi Fahandar, E. Hüllermeier, in: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017.' date_created: 2019-06-07T15:33:14Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng publication: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence status: public title: Learning to Rank based on Analogical Reasoning type: conference user_id: '49109' year: '2017' ... --- _id: '10212' author: - first_name: F. full_name: Hoffmann, F. last_name: Hoffmann - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: R. full_name: Mikut, R. last_name: Mikut citation: ama: 'Hoffmann F, Hüllermeier E, Mikut R. (Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017. In: ; 2017.' apa: Hoffmann, F., Hüllermeier, E., & Mikut, R. (2017). (Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017. bibtex: '@inproceedings{Hoffmann_Hüllermeier_Mikut_2017, title={(Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017}, author={Hoffmann, F. and Hüllermeier, Eyke and Mikut, R.}, year={2017} }' chicago: Hoffmann, F., Eyke Hüllermeier, and R. Mikut. “(Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017,” 2017. ieee: F. Hoffmann, E. Hüllermeier, and R. Mikut, “(Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017,” 2017. mla: Hoffmann, F., et al. (Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017. 2017. short: 'F. Hoffmann, E. Hüllermeier, R. Mikut, in: 2017.' date_created: 2019-06-07T15:46:10Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng status: public title: (Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017 type: conference user_id: '49109' year: '2017' ... --- _id: '10213' author: - first_name: Vitaly full_name: Melnikov, Vitaly last_name: Melnikov - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017. ; 2017:1-12.' apa: 'Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017 (pp. 1–12).' bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics}, booktitle={Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, year={2017}, pages={1–12} }' chicago: 'Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” In Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 1–12, 2017.' ieee: 'V. Melnikov and E. Hüllermeier, “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics,” in Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.' mla: 'Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.' short: 'V. Melnikov, E. Hüllermeier, in: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.' date_created: 2019-06-07T15:49:36Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 1-12 publication: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017 status: public title: 'Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics' type: conference user_id: '49109' year: '2017' ... --- _id: '10216' author: - first_name: Ammar full_name: Shaker, Ammar last_name: Shaker - first_name: W. full_name: Heldt, W. last_name: Heldt - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Shaker A, Heldt W, Hüllermeier E. Learning TSK Fuzzy Rules from Data Streams. In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia. ; 2017.' apa: Shaker, A., Heldt, W., & Hüllermeier, E. (2017). Learning TSK Fuzzy Rules from Data Streams. In Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia. bibtex: '@inproceedings{Shaker_Heldt_Hüllermeier_2017, title={Learning TSK Fuzzy Rules from Data Streams}, booktitle={Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia}, author={Shaker, Ammar and Heldt, W. and Hüllermeier, Eyke}, year={2017} }' chicago: Shaker, Ammar, W. Heldt, and Eyke Hüllermeier. “Learning TSK Fuzzy Rules from Data Streams.” In Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017. ieee: A. Shaker, W. Heldt, and E. Hüllermeier, “Learning TSK Fuzzy Rules from Data Streams,” in Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017. mla: Shaker, Ammar, et al. “Learning TSK Fuzzy Rules from Data Streams.” Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017. short: 'A. Shaker, W. Heldt, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.' date_created: 2019-06-07T16:00:10Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng publication: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia status: public title: Learning TSK Fuzzy Rules from Data Streams type: conference user_id: '49109' year: '2017' ... --- _id: '10267' author: - first_name: M. full_name: Bräuning, M. last_name: Bräuning - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: T. full_name: Keller, T. last_name: Keller - first_name: M. full_name: Glaum, M. last_name: Glaum citation: ama: Bräuning M, Hüllermeier E, Keller T, Glaum M. Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application  in accounting. European Journal of Operational Research. 2017;258(1):295-306. apa: Bräuning, M., Hüllermeier, E., Keller, T., & Glaum, M. (2017). Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application  in accounting. European Journal of Operational Research, 258(1), 295–306. bibtex: '@article{Bräuning_Hüllermeier_Keller_Glaum_2017, title={Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application  in accounting}, volume={258}, number={1}, journal={European Journal of Operational Research}, author={Bräuning, M. and Hüllermeier, Eyke and Keller, T. and Glaum, M.}, year={2017}, pages={295–306} }' chicago: 'Bräuning, M., Eyke Hüllermeier, T. Keller, and M. Glaum. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application  in Accounting.” European Journal of Operational Research 258, no. 1 (2017): 295–306.' ieee: M. Bräuning, E. Hüllermeier, T. Keller, and M. Glaum, “Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application  in accounting,” European Journal of Operational Research, vol. 258, no. 1, pp. 295–306, 2017. mla: Bräuning, M., et al. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application  in Accounting.” European Journal of Operational Research, vol. 258, no. 1, 2017, pp. 295–306. short: M. Bräuning, E. Hüllermeier, T. Keller, M. Glaum, European Journal of Operational Research 258 (2017) 295–306. date_created: 2019-06-18T15:43:40Z date_updated: 2022-01-06T06:50:33Z department: - _id: '34' - _id: '7' - _id: '355' intvolume: ' 258' issue: '1' language: - iso: eng page: 295-306 publication: European Journal of Operational Research status: public title: Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting type: journal_article user_id: '49109' volume: 258 year: '2017' ... --- _id: '10268' author: - first_name: M.-C. full_name: Platenius, M.-C. last_name: Platenius - first_name: Ammar full_name: Shaker, Ammar last_name: Shaker - first_name: M. full_name: Becker, M. last_name: Becker - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: W. full_name: Schäfer, W. last_name: Schäfer citation: ama: Platenius M-C, Shaker A, Becker M, Hüllermeier E, Schäfer W. Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic. IEEE Transactions on Software Engineering. 2017;43(8):739-759. apa: Platenius, M.-C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W. (2017). Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic. IEEE Transactions on Software Engineering, 43(8), 739–759. bibtex: '@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2017, title={Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic}, volume={43}, number={8}, journal={IEEE Transactions on Software Engineering}, author={Platenius, M.-C. and Shaker, Ammar and Becker, M. and Hüllermeier, Eyke and Schäfer, W.}, year={2017}, pages={739–759} }' chicago: 'Platenius, M.-C., Ammar Shaker, M. Becker, Eyke Hüllermeier, and W. Schäfer. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering 43, no. 8 (2017): 739–59.' ieee: M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic,” IEEE Transactions on Software Engineering, vol. 43, no. 8, pp. 739–759, 2017. mla: Platenius, M. C., et al. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering, vol. 43, no. 8, 2017, pp. 739–59. short: M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering 43 (2017) 739–759. date_created: 2019-06-18T15:47:33Z date_updated: 2022-01-06T06:50:33Z department: - _id: '34' - _id: '7' - _id: '355' intvolume: ' 43' issue: '8' language: - iso: eng page: 739-759 publication: IEEE Transactions on Software Engineering status: public title: Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic type: journal_article user_id: '49109' volume: 43 year: '2017' ... --- _id: '10269' article_number: 'abs/1712.00646 ' author: - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Hüllermeier E. From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection. The Computing Research Repository  (CoRR). 2017.' apa: 'Hüllermeier, E. (2017). From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection. The Computing Research Repository  (CoRR).' bibtex: '@article{Hüllermeier_2017, title={From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection}, number={abs/1712.00646}, journal={The Computing Research Repository  (CoRR)}, author={Hüllermeier, Eyke}, year={2017} }' chicago: 'Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy Rule-Based Systems: A Critical Reflection.” The Computing Research Repository  (CoRR), 2017.' ieee: 'E. Hüllermeier, “From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection,” The Computing Research Repository  (CoRR), 2017.' mla: 'Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy Rule-Based Systems: A Critical Reflection.” The Computing Research Repository  (CoRR), abs/1712.00646, 2017.' short: E. Hüllermeier, The Computing Research Repository  (CoRR) (2017). date_created: 2019-06-18T15:53:28Z date_updated: 2022-01-06T06:50:33Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng publication: The Computing Research Repository (CoRR) status: public title: 'From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection' type: journal_article user_id: '49109' year: '2017' ... --- _id: '24154' author: - first_name: Arunselvan full_name: Ramaswamy, Arunselvan id: '66937' last_name: Ramaswamy orcid: https://orcid.org/ 0000-0001-7547-8111 - first_name: Shalabh full_name: Bhatnagar, Shalabh last_name: Bhatnagar citation: ama: Ramaswamy A, Bhatnagar S. Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem. Stochastics. 2016;88(8):1173-1187. apa: Ramaswamy, A., & Bhatnagar, S. (2016). Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem. Stochastics, 88(8), 1173–1187. bibtex: '@article{Ramaswamy_Bhatnagar_2016, title={Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem}, volume={88}, number={8}, journal={Stochastics}, publisher={Taylor \& Francis}, author={Ramaswamy, Arunselvan and Bhatnagar, Shalabh}, year={2016}, pages={1173–1187} }' chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics 88, no. 8 (2016): 1173–87.' ieee: A. Ramaswamy and S. Bhatnagar, “Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem,” Stochastics, vol. 88, no. 8, pp. 1173–1187, 2016. mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics, vol. 88, no. 8, Taylor \& Francis, 2016, pp. 1173–87. short: A. Ramaswamy, S. Bhatnagar, Stochastics 88 (2016) 1173–1187. date_created: 2021-09-10T10:21:49Z date_updated: 2022-01-06T06:56:08Z department: - _id: '355' extern: '1' intvolume: ' 88' issue: '8' language: - iso: eng page: 1173-1187 publication: Stochastics publisher: Taylor \& Francis status: public title: Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem type: journal_article user_id: '66937' volume: 88 year: '2016' ... --- _id: '3318' author: - first_name: Vitalik full_name: Melnikov, Vitalik last_name: Melnikov - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Daniel full_name: Kaimann, Daniel id: '18949' last_name: Kaimann - first_name: 'Bernd ' full_name: 'Frick, Bernd ' last_name: Frick - first_name: ' Pritha ' full_name: 'Gupta, Pritha ' last_name: Gupta citation: ama: 'Melnikov V, Hüllermeier E, Kaimann D, Frick B, Gupta Pritha . Pairwise versus Pointwise Ranking: A Case Study. Schedae Informaticae. 2016;25. doi:10.4467/20838476si.16.006.6187' apa: 'Melnikov, V., Hüllermeier, E., Kaimann, D., Frick, B., & Gupta, Pritha . (2016). Pairwise versus Pointwise Ranking: A Case Study. Schedae Informaticae, 25. https://doi.org/10.4467/20838476si.16.006.6187' bibtex: '@article{Melnikov_Hüllermeier_Kaimann_Frick_Gupta_2016, title={Pairwise versus Pointwise Ranking: A Case Study}, volume={25}, DOI={10.4467/20838476si.16.006.6187}, journal={Schedae Informaticae}, publisher={Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego}, author={Melnikov, Vitalik and Hüllermeier, Eyke and Kaimann, Daniel and Frick, Bernd and Gupta, Pritha }, year={2016} }' chicago: 'Melnikov, Vitalik, Eyke Hüllermeier, Daniel Kaimann, Bernd Frick, and Pritha Gupta. “Pairwise versus Pointwise Ranking: A Case Study.” Schedae Informaticae 25 (2016). https://doi.org/10.4467/20838476si.16.006.6187.' ieee: 'V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, and Pritha Gupta, “Pairwise versus Pointwise Ranking: A Case Study,” Schedae Informaticae, vol. 25, 2016.' mla: 'Melnikov, Vitalik, et al. “Pairwise versus Pointwise Ranking: A Case Study.” Schedae Informaticae, vol. 25, Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego, 2016, doi:10.4467/20838476si.16.006.6187.' short: V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, Pritha Gupta, Schedae Informaticae 25 (2016). date_created: 2018-06-22T14:49:40Z date_updated: 2022-01-06T06:59:10Z ddc: - '000' department: - _id: '355' - _id: '183' doi: 10.4467/20838476si.16.006.6187 file: - access_level: closed content_type: application/pdf creator: ups date_created: 2018-11-02T15:54:38Z date_updated: 2018-11-02T15:54:38Z file_id: '5317' file_name: roz-6-Melnikov.pdf file_size: 1002478 relation: main_file success: 1 file_date_updated: 2018-11-02T15:54:38Z has_accepted_license: '1' intvolume: ' 25' language: - iso: eng project: - _id: '3' name: SFB 901 - Project Area B - _id: '11' name: SFB 901 - Subproject B3 - _id: '8' name: SFB 901 - Subproject A4 - _id: '1' name: SFB 901 - _id: '2' name: SFB 901 - Project Area A publication: Schedae Informaticae publication_identifier: issn: - 2083-8476 publication_status: published publisher: Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego status: public title: 'Pairwise versus Pointwise Ranking: A Case Study' type: journal_article user_id: '15504' volume: 25 year: '2016' ... --- _id: '190' abstract: - lang: eng text: Today, software components are provided by global markets in the form of services. In order to optimally satisfy service requesters and service providers, adequate techniques for automatic service matching are needed. However, a requester’s requirements may be vague and the information available about a provided service may be incomplete. As a consequence, fuzziness is induced into the matching procedure. The contribution of this paper is the development of a systematic matching procedure that leverages concepts and techniques from fuzzy logic and possibility theory based on our formal distinction between different sources and types of fuzziness in the context of service matching. In contrast to existing methods, our approach is able to deal with imprecision and incompleteness in service specifications and to inform users about the extent of induced fuzziness in order to improve the user’s decision-making. We demonstrate our approach on the example of specifications for service reputation based on ratings given by previous users. Our evaluation based on real service ratings shows the utility and applicability of our approach. author: - first_name: Marie Christin full_name: Platenius, Marie Christin last_name: Platenius - first_name: Ammar full_name: Shaker, Ammar last_name: Shaker - first_name: Matthias full_name: Becker, Matthias last_name: Becker - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: Wilhelm full_name: Schäfer, Wilhelm last_name: Schäfer citation: ama: Platenius MC, Shaker A, Becker M, Hüllermeier E, Schäfer W. Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017. 2016;(8):739-759. doi:10.1109/TSE.2016.2632115 apa: Platenius, M. C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W. (2016). Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, (8), 739–759. https://doi.org/10.1109/TSE.2016.2632115 bibtex: '@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2016, title={Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic}, DOI={10.1109/TSE.2016.2632115}, number={8}, journal={IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017}, publisher={IEEE}, author={Platenius, Marie Christin and Shaker, Ammar and Becker, Matthias and Hüllermeier, Eyke and Schäfer, Wilhelm}, year={2016}, pages={739–759} }' chicago: 'Platenius, Marie Christin, Ammar Shaker, Matthias Becker, Eyke Hüllermeier, and Wilhelm Schäfer. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, no. 8 (2016): 739–59. https://doi.org/10.1109/TSE.2016.2632115.' ieee: M. C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic,” IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017, no. 8, pp. 739–759, 2016. mla: Platenius, Marie Christin, et al. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, no. 8, IEEE, 2016, pp. 739–59, doi:10.1109/TSE.2016.2632115. short: M.C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017 (2016) 739–759. date_created: 2017-10-17T12:41:29Z date_updated: 2022-01-06T06:53:57Z ddc: - '040' department: - _id: '355' doi: 10.1109/TSE.2016.2632115 file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-21T12:30:31Z date_updated: 2018-03-21T12:30:31Z file_id: '1529' file_name: 190-07755807.pdf file_size: 5225413 relation: main_file success: 1 file_date_updated: 2018-03-21T12:30:31Z has_accepted_license: '1' issue: '8' language: - iso: eng page: 739-759 project: - _id: '1' name: SFB 901 - _id: '9' name: SFB 901 - Subprojekt B1 - _id: '10' name: SFB 901 - Subprojekt B2 - _id: '11' name: SFB 901 - Subprojekt B3 - _id: '3' name: SFB 901 - Project Area B publication: IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017 publisher: IEEE status: public title: Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic type: journal_article user_id: '15504' year: '2016' ... --- _id: '184' abstract: - lang: eng text: In this paper, we propose a framework for a class of learning problems that we refer to as “learning to aggregate”. Roughly, learning-to-aggregate problems are supervised machine learning problems, in which instances are represented in the form of a composition of a (variable) number on constituents; such compositions are associated with an evaluation, score, or label, which is the target of the prediction task, and which can presumably be modeled in the form of a suitable aggregation of the properties of its constituents. Our learning-to-aggregate framework establishes a close connection between machine learning and a branch of mathematics devoted to the systematic study of aggregation functions. We specifically focus on a class of functions called uninorms, which combine conjunctive and disjunctive modes of aggregation. Experimental results for a corresponding model are presented for a review data set, for which the aggregation problem consists of combining different reviewer opinions about a paper into an overall decision of acceptance or rejection. author: - first_name: Vitaly full_name: Melnikov, Vitaly id: '58747' last_name: Melnikov - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Melnikov V, Hüllermeier E. Learning to Aggregate Using Uninorms. In: Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016). LNCS. ; 2016:756-771. doi:10.1007/978-3-319-46227-1_47' apa: Melnikov, V., & Hüllermeier, E. (2016). Learning to Aggregate Using Uninorms. In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016) (pp. 756–771). https://doi.org/10.1007/978-3-319-46227-1_47 bibtex: '@inproceedings{Melnikov_Hüllermeier_2016, series={LNCS}, title={Learning to Aggregate Using Uninorms}, DOI={10.1007/978-3-319-46227-1_47}, booktitle={Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016)}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, year={2016}, pages={756–771}, collection={LNCS} }' chicago: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.” In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 756–71. LNCS, 2016. https://doi.org/10.1007/978-3-319-46227-1_47. ieee: V. Melnikov and E. Hüllermeier, “Learning to Aggregate Using Uninorms,” in Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771. mla: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.” Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–71, doi:10.1007/978-3-319-46227-1_47. short: 'V. Melnikov, E. Hüllermeier, in: Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771.' date_created: 2017-10-17T12:41:27Z date_updated: 2022-01-06T06:53:32Z ddc: - '040' department: - _id: '355' doi: 10.1007/978-3-319-46227-1_47 file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-21T12:32:44Z date_updated: 2018-03-21T12:32:44Z file_id: '1533' file_name: 184-chp_3A10.1007_2F978-3-319-46227-1_47.pdf file_size: 472159 relation: main_file success: 1 file_date_updated: 2018-03-21T12:32:44Z has_accepted_license: '1' language: - iso: eng page: 756-771 project: - _id: '1' name: SFB 901 - _id: '11' name: SFB 901 - Subprojekt B3 - _id: '3' name: SFB 901 - Project Area B publication: Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016) series_title: LNCS status: public title: Learning to Aggregate Using Uninorms type: conference user_id: '15504' year: '2016' ... --- _id: '10785' author: - first_name: J. full_name: Fürnkranz, J. last_name: Fürnkranz - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. Encyclopedia of Machine Learning and Data Mining. Springer; 2016.' apa: Fürnkranz, J., & Hüllermeier, E. (2016). Preference Learning. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining. Springer. bibtex: '@inbook{Fürnkranz_Hüllermeier_2016, title={Preference Learning}, booktitle={Encyclopedia of Machine Learning and Data Mining}, publisher={Springer}, author={Fürnkranz, J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors}, year={2016} }' chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb. Springer, 2016. ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia of Machine Learning and Data Mining, C. Sammut and G. I. Webb, Eds. Springer, 2016. mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer, 2016. short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2016.' date_created: 2019-07-10T16:00:23Z date_updated: 2022-01-06T06:50:50Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: C. full_name: Sammut, C. last_name: Sammut - first_name: G.I. full_name: Webb, G.I. last_name: Webb language: - iso: eng publication: Encyclopedia of Machine Learning and Data Mining publisher: Springer status: public title: Preference Learning type: encyclopedia_article user_id: '49109' year: '2016' ... --- _id: '15400' author: - first_name: C. full_name: Labreuche, C. last_name: Labreuche - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: P. full_name: Vojtas, P. last_name: Vojtas - first_name: A. full_name: Fallah Tehrani, A. last_name: Fallah Tehrani citation: ama: 'Labreuche C, Hüllermeier E, Vojtas P, Fallah Tehrani A. On the identifiability of models  in multi-criteria preference learning. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany. ; 2016.' apa: Labreuche, C., Hüllermeier, E., Vojtas, P., & Fallah Tehrani, A. (2016). On the identifiability of models  in multi-criteria preference learning. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany. bibtex: '@inproceedings{Labreuche_Hüllermeier_Vojtas_Fallah Tehrani_2016, title={On the identifiability of models  in multi-criteria preference learning}, booktitle={in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany}, author={Labreuche, C. and Hüllermeier, Eyke and Vojtas, P. and Fallah Tehrani, A.}, editor={Busa-Fekete, R. and Hüllermeier, Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }' chicago: Labreuche, C., Eyke Hüllermeier, P. Vojtas, and A. Fallah Tehrani. “On the Identifiability of Models  in Multi-Criteria Preference Learning.” In In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016. ieee: C. Labreuche, E. Hüllermeier, P. Vojtas, and A. Fallah Tehrani, “On the identifiability of models  in multi-criteria preference learning,” in in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016. mla: Labreuche, C., et al. “On the Identifiability of Models  in Multi-Criteria Preference Learning.” In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete et al., 2016. short: 'C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.' date_created: 2019-12-19T16:02:19Z date_updated: 2022-01-06T06:52:23Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: R. full_name: Busa-Fekete, R. last_name: Busa-Fekete - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: V. full_name: Mousseau, V. last_name: Mousseau - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt language: - iso: eng publication: in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany status: public title: On the identifiability of models in multi-criteria preference learning type: conference user_id: '49109' year: '2016' ... --- _id: '15401' author: - first_name: D. full_name: Schäfer, D. last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Schäfer D, Hüllermeier E. Preference -based reinforcement learning using dyad ranking. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. In Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany. ; 2016.' apa: Schäfer, D., & Hüllermeier, E. (2016). Preference -based reinforcement learning using dyad ranking. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), in Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany. bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Preference -based reinforcement learning using dyad ranking}, booktitle={in Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany}, author={Schäfer, D. and Hüllermeier, Eyke}, editor={Busa-Fekete, R. and Hüllermeier, Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }' chicago: Schäfer, D., and Eyke Hüllermeier. “Preference -Based Reinforcement Learning Using Dyad Ranking.” In In Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, edited by R. Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016. ieee: D. Schäfer and E. Hüllermeier, “Preference -based reinforcement learning using dyad ranking,” in in Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, 2016. mla: Schäfer, D., and Eyke Hüllermeier. “Preference -Based Reinforcement Learning Using Dyad Ranking.” In Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, edited by R. Busa-Fekete et al., 2016. short: 'D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany, 2016.' date_created: 2019-12-19T16:33:45Z date_updated: 2022-01-06T06:52:23Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: R. full_name: Busa-Fekete, R. last_name: Busa-Fekete - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: V. full_name: Mousseau, V. last_name: Mousseau - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt language: - iso: eng publication: in Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany status: public title: Preference -based reinforcement learning using dyad ranking type: conference user_id: '49109' year: '2016' ... --- _id: '15402' author: - first_name: Ines full_name: Couso, Ines last_name: Couso - first_name: Mohsen full_name: Ahmadi Fahandar, Mohsen last_name: Ahmadi Fahandar - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Couso I, Ahmadi Fahandar M, Hüllermeier E. Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany. ; 2016.' apa: 'Couso, I., Ahmadi Fahandar, M., & Hüllermeier, E. (2016). Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany.' bibtex: '@inproceedings{Couso_Ahmadi Fahandar_Hüllermeier_2016, title={Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators}, booktitle={in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany}, author={Couso, Ines and Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke}, editor={Busa-Fekete, R. and Hüllermeier, Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }' chicago: 'Couso, Ines, Mohsen Ahmadi Fahandar, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016.' ieee: 'I. Couso, M. Ahmadi Fahandar, and E. Hüllermeier, “Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators,” in in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.' mla: 'Couso, Ines, et al. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, edited by R. Busa-Fekete et al., 2016.' short: 'I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), In Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany, 2016.' date_created: 2019-12-19T16:37:06Z date_updated: 2022-01-06T06:52:23Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: R. full_name: Busa-Fekete, R. last_name: Busa-Fekete - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: V. full_name: Mousseau, V. last_name: Mousseau - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt language: - iso: eng publication: in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany status: public title: 'Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators' type: conference user_id: '49109' year: '2016' ... --- _id: '15403' author: - first_name: S. full_name: Lu, S. last_name: Lu - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Lu S, Hüllermeier E. Support vector classification on noisy data using fuzzy superset losses. In: Hüllermeier E, Hoffmann F, Mikut R, eds. In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany. KIT Scientific Publishing; 2016:1-8.' apa: Lu, S., & Hüllermeier, E. (2016). Support vector classification on noisy data using fuzzy superset losses. In E. Hüllermeier, F. Hoffmann, & R. Mikut (Eds.), in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany (pp. 1–8). KIT Scientific Publishing. bibtex: '@inproceedings{Lu_Hüllermeier_2016, title={Support vector classification on noisy data using fuzzy superset losses}, booktitle={in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany}, publisher={KIT Scientific Publishing}, author={Lu, S. and Hüllermeier, Eyke}, editor={Hüllermeier, Eyke and Hoffmann, F. and Mikut, R.Editors}, year={2016}, pages={1–8} }' chicago: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data Using Fuzzy Superset Losses.” In In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, edited by Eyke Hüllermeier, F. Hoffmann, and R. Mikut, 1–8. KIT Scientific Publishing, 2016. ieee: S. Lu and E. Hüllermeier, “Support vector classification on noisy data using fuzzy superset losses,” in in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, 2016, pp. 1–8. mla: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data Using Fuzzy Superset Losses.” In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, edited by Eyke Hüllermeier et al., KIT Scientific Publishing, 2016, pp. 1–8. short: 'S. Lu, E. Hüllermeier, in: E. Hüllermeier, F. Hoffmann, R. Mikut (Eds.), In Proceedings 26th Workshop Computational Intelligence, Dortmund Germany, KIT Scientific Publishing, 2016, pp. 1–8.' date_created: 2019-12-19T16:40:33Z date_updated: 2022-01-06T06:52:23Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: F. full_name: Hoffmann, F. last_name: Hoffmann - first_name: R. full_name: Mikut, R. last_name: Mikut language: - iso: eng page: 1-8 publication: in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany publisher: KIT Scientific Publishing status: public title: Support vector classification on noisy data using fuzzy superset losses type: conference user_id: '49109' year: '2016' ... --- _id: '15404' author: - first_name: D. full_name: Schäfer, D. last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany. ; 2016.' apa: Schäfer, D., & Hüllermeier, E. (2016). Plackett-Luce networks for dyad ranking. In in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany. bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Plackett-Luce networks for dyad ranking}, booktitle={in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany}, author={Schäfer, D. and Hüllermeier, Eyke}, year={2016} }' chicago: Schäfer, D., and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.” In In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016. ieee: D. Schäfer and E. Hüllermeier, “Plackett-Luce networks for dyad ranking,” in in Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016. mla: Schäfer, D., and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.” In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016. short: 'D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany, 2016.' date_created: 2019-12-19T16:43:27Z date_updated: 2022-01-06T06:52:23Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng publication: in Workshop LWDA "Lernen, Wissen, Daten, Analysen" Potsdam, Germany status: public title: Plackett-Luce networks for dyad ranking type: conference user_id: '49109' year: '2016' ... --- _id: '15111' author: - first_name: Karlson full_name: Pfannschmidt, Karlson id: '13472' last_name: Pfannschmidt orcid: 0000-0001-9407-7903 - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: S. full_name: Held, S. last_name: Held - first_name: R. full_name: Neiger, R. last_name: Neiger citation: ama: 'Pfannschmidt K, Hüllermeier E, Held S, Neiger R. Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts. In: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands. Springer; 2016:450-461.' apa: Pfannschmidt, K., Hüllermeier, E., Held, S., & Neiger, R. (2016). Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts. In In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands (pp. 450–461). Springer. bibtex: '@inproceedings{Pfannschmidt_Hüllermeier_Held_Neiger_2016, title={Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts}, booktitle={In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands}, publisher={Springer}, author={Pfannschmidt, Karlson and Hüllermeier, Eyke and Held, S. and Neiger, R.}, year={2016}, pages={450–461} }' chicago: Pfannschmidt, Karlson, Eyke Hüllermeier, S. Held, and R. Neiger. “Evaluating Tests in Medical  Diagnosis-Combining Machine Learning with Game-Theoretical Concepts.” In In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, 450–61. Springer, 2016. ieee: K. Pfannschmidt, E. Hüllermeier, S. Held, and R. Neiger, “Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts,” in In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, 2016, pp. 450–461. mla: Pfannschmidt, Karlson, et al. “Evaluating Tests in Medical  Diagnosis-Combining Machine Learning with Game-Theoretical Concepts.” In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–61. short: 'K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–461.' date_created: 2019-11-21T16:42:47Z date_updated: 2022-01-06T06:52:15Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 450-461 publication: In Proceedings IPMU 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands publisher: Springer status: public title: Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical concepts type: conference user_id: '49109' year: '2016' ... --- _id: '16041' author: - first_name: M. full_name: Leinweber, M. last_name: Leinweber - first_name: T. full_name: Fober, T. last_name: Fober - first_name: M. full_name: Strickert, M. last_name: Strickert - first_name: L. full_name: Baumgärtner, L. last_name: Baumgärtner - first_name: G. full_name: Klebe, G. last_name: Klebe - first_name: B. full_name: Freisleben, B. last_name: Freisleben - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Leinweber M, Fober T, Strickert M, et al. CavSimBase: A database for large scale comparison of protein binding sites. IEEE Transactions on Knowledge and Data Engineering. 2016;28(6):1423-1434.' apa: 'Leinweber, M., Fober, T., Strickert, M., Baumgärtner, L., Klebe, G., Freisleben, B., & Hüllermeier, E. (2016). CavSimBase: A database for large scale comparison of protein binding sites. IEEE Transactions on Knowledge and Data Engineering, 28(6), 1423–1434.' bibtex: '@article{Leinweber_Fober_Strickert_Baumgärtner_Klebe_Freisleben_Hüllermeier_2016, title={CavSimBase: A database for large scale comparison of protein binding sites}, volume={28}, number={6}, journal={IEEE Transactions on Knowledge and Data Engineering}, author={Leinweber, M. and Fober, T. and Strickert, M. and Baumgärtner, L. and Klebe, G. and Freisleben, B. and Hüllermeier, Eyke}, year={2016}, pages={1423–1434} }' chicago: 'Leinweber, M., T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, and Eyke Hüllermeier. “CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites.” IEEE Transactions on Knowledge and Data Engineering 28, no. 6 (2016): 1423–34.' ieee: 'M. Leinweber et al., “CavSimBase: A database for large scale comparison of protein binding sites,” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, pp. 1423–1434, 2016.' mla: 'Leinweber, M., et al. “CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites.” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, 2016, pp. 1423–34.' short: M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016) 1423–1434. date_created: 2020-02-24T16:04:59Z date_updated: 2022-01-06T06:52:42Z department: - _id: '34' - _id: '7' - _id: '355' intvolume: ' 28' issue: '6' language: - iso: eng page: 1423-1434 publication: IEEE Transactions on Knowledge and Data Engineering status: public title: 'CavSimBase: A database for large scale comparison of protein binding sites' type: journal_article user_id: '49109' volume: 28 year: '2016' ... --- _id: '141' author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr citation: ama: Mohr F. Towards Automated Service Composition Under Quality Constraints. Universität Paderborn; 2016. doi:10.17619/UNIPB/1-171 apa: Mohr, F. (2016). Towards Automated Service Composition Under Quality Constraints. Universität Paderborn. https://doi.org/10.17619/UNIPB/1-171 bibtex: '@book{Mohr_2016, title={Towards Automated Service Composition Under Quality Constraints}, DOI={10.17619/UNIPB/1-171}, publisher={Universität Paderborn}, author={Mohr, Felix}, year={2016} }' chicago: Mohr, Felix. Towards Automated Service Composition Under Quality Constraints. Universität Paderborn, 2016. https://doi.org/10.17619/UNIPB/1-171. ieee: F. Mohr, Towards Automated Service Composition Under Quality Constraints. Universität Paderborn, 2016. mla: Mohr, Felix. Towards Automated Service Composition Under Quality Constraints. Universität Paderborn, 2016, doi:10.17619/UNIPB/1-171. short: F. Mohr, Towards Automated Service Composition Under Quality Constraints, Universität Paderborn, 2016. date_created: 2017-10-17T12:41:19Z date_updated: 2022-01-06T06:51:55Z department: - _id: '355' doi: 10.17619/UNIPB/1-171 project: - _id: '1' name: SFB 901 - _id: '10' name: SFB 901 - Subprojekt B2 - _id: '3' name: SFB 901 - Project Area B publisher: Universität Paderborn status: public supervisor: - first_name: Hans full_name: Kleine Büning, Hans last_name: Kleine Büning title: Towards Automated Service Composition Under Quality Constraints type: dissertation user_id: '477' year: '2016' ... --- _id: '10214' author: - first_name: J. full_name: Fürnkranz, J. last_name: Fürnkranz - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. Encyclopedia of Machine Learning and Data Mining. Springer; 2016.' apa: Fürnkranz, J., & Hüllermeier, E. (2016). Preference Learning. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining. Springer. bibtex: '@inbook{Fürnkranz_Hüllermeier_2016, title={Preference Learning}, booktitle={Encyclopedia of Machine Learning and Data Mining}, publisher={Springer}, author={Fürnkranz, J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors}, year={2016} }' chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb. Springer, 2016. ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia of Machine Learning and Data Mining, C. Sammut and G. I. Webb, Eds. Springer, 2016. mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer, 2016. short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2016.' date_created: 2019-06-07T15:52:19Z date_updated: 2022-01-06T06:50:31Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: C. full_name: Sammut, C. last_name: Sammut - first_name: G.I. full_name: Webb, G.I. last_name: Webb language: - iso: eng publication: Encyclopedia of Machine Learning and Data Mining publisher: Springer status: public title: Preference Learning type: book_chapter user_id: '49109' year: '2016' ... --- _id: '10221' citation: ama: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany.; 2016. apa: Hoffmann, F., Hüllermeier, E., & Mikut, R. (Eds.). (2016). Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany. bibtex: '@book{Hoffmann_Hüllermeier_Mikut_2016, title={ Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany}, year={2016} }' chicago: Hoffmann, F., Eyke Hüllermeier, and R. Mikut, eds. Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany, 2016. ieee: F. Hoffmann, E. Hüllermeier, and R. Mikut, Eds., Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany. 2016. mla: Hoffmann, F., et al., editors. Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany. 2016. short: F. Hoffmann, E. Hüllermeier, R. Mikut, eds., Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany, 2016. date_created: 2019-06-11T14:40:45Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: F. full_name: Hoffmann, F. last_name: Hoffmann - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: R. full_name: Mikut, R. last_name: Mikut language: - iso: eng status: public title: ' Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany' type: conference_editor user_id: '49109' year: '2016' ... --- _id: '10222' author: - first_name: K. full_name: Jasinska, K. last_name: Jasinska - first_name: K. full_name: Dembczynski, K. last_name: Dembczynski - first_name: Robert full_name: Busa-Fekete, Robert last_name: Busa-Fekete - first_name: Timo full_name: Klerx, Timo last_name: Klerx - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Jasinska K, Dembczynski K, Busa-Fekete R, Klerx T, Hüllermeier E. Extreme F-measure maximization using sparse probability estimates . In: Balcan MF, Weinberger KQ, eds. Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA. ; 2016.' apa: Jasinska, K., Dembczynski, K., Busa-Fekete, R., Klerx, T., & Hüllermeier, E. (2016). Extreme F-measure maximization using sparse probability estimates . In M. F. Balcan & K. Q. Weinberger (Eds.), Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA. bibtex: '@inproceedings{Jasinska_Dembczynski_Busa-Fekete_Klerx_Hüllermeier_2016, title={Extreme F-measure maximization using sparse probability estimates }, booktitle={Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA}, author={Jasinska, K. and Dembczynski, K. and Busa-Fekete, Robert and Klerx, Timo and Hüllermeier, Eyke}, editor={Balcan, M.F. and Weinberger, K.Q.Editors}, year={2016} }' chicago: Jasinska, K., K. Dembczynski, Robert Busa-Fekete, Timo Klerx, and Eyke Hüllermeier. “Extreme F-Measure Maximization Using Sparse Probability Estimates .” In Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, edited by M.F. Balcan and K.Q. Weinberger, 2016. ieee: K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, and E. Hüllermeier, “Extreme F-measure maximization using sparse probability estimates ,” in Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, 2016. mla: Jasinska, K., et al. “Extreme F-Measure Maximization Using Sparse Probability Estimates .” Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, edited by M.F. Balcan and K.Q. Weinberger, 2016. short: 'K. Jasinska, K. Dembczynski, R. Busa-Fekete, T. Klerx, E. Hüllermeier, in: M.F. Balcan, K.Q. Weinberger (Eds.), Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA, 2016.' date_created: 2019-06-11T14:47:31Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: M.F. full_name: Balcan, M.F. last_name: Balcan - first_name: K.Q. full_name: Weinberger, K.Q. last_name: Weinberger language: - iso: eng publication: Proceedings ICML-2016, 33th International Conference on Machine Learning, New York, USA status: public title: 'Extreme F-measure maximization using sparse probability estimates ' type: conference user_id: '49109' year: '2016' ... --- _id: '10223' author: - first_name: Vitaly full_name: Melnikov, Vitaly id: '58747' last_name: Melnikov - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Melnikov V, Hüllermeier E. Learning to aggregate using uninorms,  in Proceedings ECML/PKDD-2016. In: European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy. ; 2016:756-771.' apa: Melnikov, V., & Hüllermeier, E. (2016). Learning to aggregate using uninorms,  in Proceedings ECML/PKDD-2016. In European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy (pp. 756–771). bibtex: '@inproceedings{Melnikov_Hüllermeier_2016, title={Learning to aggregate using uninorms,  in Proceedings ECML/PKDD-2016}, booktitle={European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, year={2016}, pages={756–771} }' chicago: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms,  in Proceedings ECML/PKDD-2016.” In European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 756–71, 2016. ieee: V. Melnikov and E. Hüllermeier, “Learning to aggregate using uninorms,  in Proceedings ECML/PKDD-2016,” in European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy, 2016, pp. 756–771. mla: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms,  in Proceedings ECML/PKDD-2016.” European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 756–71. short: 'V. Melnikov, E. Hüllermeier, in: European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 756–771.' date_created: 2019-06-11T14:51:30Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 756-771 publication: European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy status: public title: Learning to aggregate using uninorms, in Proceedings ECML/PKDD-2016 type: conference user_id: '49109' year: '2016' ... --- _id: '10224' author: - first_name: K. full_name: Dembczynski, K. last_name: Dembczynski - first_name: W. full_name: Kotlowski, W. last_name: Kotlowski - first_name: W. full_name: Waegeman, W. last_name: Waegeman - first_name: Robert full_name: Busa-Fekete, Robert last_name: Busa-Fekete - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Dembczynski K, Kotlowski W, Waegeman W, Busa-Fekete R, Hüllermeier E. Consistency of probalistic classifier trees. In: In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy. ; 2016:511-526.' apa: Dembczynski, K., Kotlowski, W., Waegeman, W., Busa-Fekete, R., & Hüllermeier, E. (2016). Consistency of probalistic classifier trees. In In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy (pp. 511–526). bibtex: '@inproceedings{Dembczynski_Kotlowski_Waegeman_Busa-Fekete_Hüllermeier_2016, title={Consistency of probalistic classifier trees}, booktitle={In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy}, author={Dembczynski, K. and Kotlowski, W. and Waegeman, W. and Busa-Fekete, Robert and Hüllermeier, Eyke}, year={2016}, pages={511–526} }' chicago: Dembczynski, K., W. Kotlowski, W. Waegeman, Robert Busa-Fekete, and Eyke Hüllermeier. “Consistency of Probalistic Classifier Trees.” In In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 511–26, 2016. ieee: K. Dembczynski, W. Kotlowski, W. Waegeman, R. Busa-Fekete, and E. Hüllermeier, “Consistency of probalistic classifier trees,” in In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy, 2016, pp. 511–526. mla: Dembczynski, K., et al. “Consistency of Probalistic Classifier Trees.” In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 511–26. short: 'K. Dembczynski, W. Kotlowski, W. Waegeman, R. Busa-Fekete, E. Hüllermeier, in: In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 511–526.' date_created: 2019-06-11T14:56:02Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 511-526 publication: In Proceedings ECML/PKDD European Conference on Maschine Learning and Knowledge Discovery in Databases, Part II, Riva del Garda, Italy status: public title: Consistency of probalistic classifier trees type: conference user_id: '49109' year: '2016' ... --- _id: '10225' author: - first_name: Aulon full_name: Shabani, Aulon last_name: Shabani - first_name: Adil full_name: Paul, Adil last_name: Paul - first_name: R. full_name: Platon, R. last_name: Platon - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Shabani A, Paul A, Platon R, Hüllermeier E. Predicting the electricity consumption of buildings: An improved CBR approach. In: In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA. ; 2016:356-369.' apa: 'Shabani, A., Paul, A., Platon, R., & Hüllermeier, E. (2016). Predicting the electricity consumption of buildings: An improved CBR approach. In In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA (pp. 356–369).' bibtex: '@inproceedings{Shabani_Paul_Platon_Hüllermeier_2016, title={Predicting the electricity consumption of buildings: An improved CBR approach}, booktitle={In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA}, author={Shabani, Aulon and Paul, Adil and Platon, R. and Hüllermeier, Eyke}, year={2016}, pages={356–369} }' chicago: 'Shabani, Aulon, Adil Paul, R. Platon, and Eyke Hüllermeier. “Predicting the Electricity Consumption of Buildings: An Improved CBR Approach.” In In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 356–69, 2016.' ieee: 'A. Shabani, A. Paul, R. Platon, and E. Hüllermeier, “Predicting the electricity consumption of buildings: An improved CBR approach,” in In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016, pp. 356–369.' mla: 'Shabani, Aulon, et al. “Predicting the Electricity Consumption of Buildings: An Improved CBR Approach.” In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016, pp. 356–69.' short: 'A. Shabani, A. Paul, R. Platon, E. Hüllermeier, in: In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA, 2016, pp. 356–369.' date_created: 2019-06-11T15:00:49Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 356-369 publication: In Proceedings ICCBR, 24th International Conference on Case-Based Reasoning, Atlanta, GA, USA status: public title: 'Predicting the electricity consumption of buildings: An improved CBR approach' type: conference user_id: '49109' year: '2016' ... --- _id: '10226' author: - first_name: Karlson full_name: Pfannschmidt, Karlson id: '13472' last_name: Pfannschmidt orcid: 0000-0001-9407-7903 - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: S. full_name: Held, S. last_name: Held - first_name: R. full_name: Neiger, R. last_name: Neiger citation: ama: 'Pfannschmidt K, Hüllermeier E, Held S, Neiger R. Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts. In: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands. Springer; 2016:450-461.' apa: Pfannschmidt, K., Hüllermeier, E., Held, S., & Neiger, R. (2016). Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts. In In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands (pp. 450–461). Springer. bibtex: '@inproceedings{Pfannschmidt_Hüllermeier_Held_Neiger_2016, title={Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts}, booktitle={In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands}, publisher={Springer}, author={Pfannschmidt, Karlson and Hüllermeier, Eyke and Held, S. and Neiger, R.}, year={2016}, pages={450–461} }' chicago: Pfannschmidt, Karlson, Eyke Hüllermeier, S. Held, and R. Neiger. “Evaluating Tests in Medical  Diagnosis-Combining Machine Learning with Game-Theoretical Concepts.” In In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, 450–61. Springer, 2016. ieee: K. Pfannschmidt, E. Hüllermeier, S. Held, and R. Neiger, “Evaluating tests in medical  diagnosis-Combining machine learning with game-theoretical concepts,” in In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, 2016, pp. 450–461. mla: Pfannschmidt, Karlson, et al. “Evaluating Tests in Medical  Diagnosis-Combining Machine Learning with Game-Theoretical Concepts.” In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–61. short: 'K. Pfannschmidt, E. Hüllermeier, S. Held, R. Neiger, in: In Proceedings IPMU 16th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands, Springer, 2016, pp. 450–461.' date_created: 2019-06-11T15:11:54Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 450-461 publication: In Proceedings IPMU 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Part 1, Eindhoven, The Netherlands publisher: Springer status: public title: Evaluating tests in medical diagnosis-Combining machine learning with game-theoretical concepts type: conference user_id: '49109' year: '2016' ... --- _id: '10227' author: - first_name: C. full_name: Labreuche, C. last_name: Labreuche - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: P. full_name: Vojtas, P. last_name: Vojtas - first_name: A. full_name: Fallah Tehrani, A. last_name: Fallah Tehrani citation: ama: 'Labreuche C, Hüllermeier E, Vojtas P, Fallah Tehrani A. On the Identifiability of models in multi-criteria preference learning . In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.' apa: Labreuche, C., Hüllermeier, E., Vojtas, P., & Fallah Tehrani, A. (2016). On the Identifiability of models in multi-criteria preference learning . In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. bibtex: '@inproceedings{Labreuche_Hüllermeier_Vojtas_Fallah Tehrani_2016, title={On the Identifiability of models in multi-criteria preference learning }, booktitle={Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning}, author={Labreuche, C. and Hüllermeier, Eyke and Vojtas, P. and Fallah Tehrani, A.}, editor={Busa-Fekete, Robert and Hüllermeier, Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }' chicago: Labreuche, C., Eyke Hüllermeier, P. Vojtas, and A. Fallah Tehrani. “On the Identifiability of Models in Multi-Criteria Preference Learning .” In Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016. ieee: C. Labreuche, E. Hüllermeier, P. Vojtas, and A. Fallah Tehrani, “On the Identifiability of models in multi-criteria preference learning ,” in Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016. mla: Labreuche, C., et al. “On the Identifiability of Models in Multi-Criteria Preference Learning .” Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete et al., 2016. short: 'C. Labreuche, E. Hüllermeier, P. Vojtas, A. Fallah Tehrani, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.' date_created: 2019-06-11T15:34:48Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: Robert full_name: Busa-Fekete, Robert last_name: Busa-Fekete - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: V. full_name: Mousseau, V. last_name: Mousseau - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt language: - iso: eng publication: Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning status: public title: 'On the Identifiability of models in multi-criteria preference learning ' type: conference user_id: '49109' year: '2016' ... --- _id: '10228' author: - first_name: Dirk full_name: Schäfer, Dirk last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.' apa: Schäfer, D., & Hüllermeier, E. (2016). Preference-Based Reinforcement Learning Using Dyad Ranking. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Preference-Based Reinforcement Learning Using Dyad Ranking}, booktitle={Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning}, author={Schäfer, Dirk and Hüllermeier, Eyke}, editor={Busa-Fekete, Robert and Hüllermeier, Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }' chicago: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” In Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016. ieee: D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using Dyad Ranking,” in Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016. mla: Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete et al., 2016. short: 'D. Schäfer, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.' date_created: 2019-06-11T15:37:51Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: Robert full_name: Busa-Fekete, Robert last_name: Busa-Fekete - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: V. full_name: Mousseau, V. last_name: Mousseau - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt language: - iso: eng publication: Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning status: public title: Preference-Based Reinforcement Learning Using Dyad Ranking type: conference user_id: '49109' year: '2016' ... --- _id: '10229' author: - first_name: Ines full_name: Couso, Ines last_name: Couso - first_name: Mohsen full_name: Ahmadi Fahandar, Mohsen last_name: Ahmadi Fahandar - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Couso I, Ahmadi Fahandar M, Hüllermeier E. Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.' apa: 'Couso, I., Ahmadi Fahandar, M., & Hüllermeier, E. (2016). Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In R. Busa-Fekete, E. Hüllermeier, V. Mousseau, & K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning.' bibtex: '@inproceedings{Couso_Ahmadi Fahandar_Hüllermeier_2016, title={Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators}, booktitle={Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning}, author={Couso, Ines and Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke}, editor={Busa-Fekete, Robert and Hüllermeier, Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }' chicago: 'Couso, Ines, Mohsen Ahmadi Fahandar, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016.' ieee: 'I. Couso, M. Ahmadi Fahandar, and E. Hüllermeier, “Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators,” in Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.' mla: 'Couso, Ines, et al. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete et al., 2016.' short: 'I. Couso, M. Ahmadi Fahandar, E. Hüllermeier, in: R. Busa-Fekete, E. Hüllermeier, V. Mousseau, K. Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, 2016.' date_created: 2019-06-11T15:41:55Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: Robert full_name: Busa-Fekete, Robert last_name: Busa-Fekete - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: V. full_name: Mousseau, V. last_name: Mousseau - first_name: Karlson full_name: Pfannschmidt, Karlson last_name: Pfannschmidt language: - iso: eng publication: Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning status: public title: 'Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators' type: conference user_id: '49109' year: '2016' ... --- _id: '10230' author: - first_name: S. full_name: Lu, S. last_name: Lu - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Lu S, Hüllermeier E. Support vector classification on noisy data using fuzzy supersets losses. In: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing. ; 2016:1-8.' apa: Lu, S., & Hüllermeier, E. (2016). Support vector classification on noisy data using fuzzy supersets losses. In F. Hoffmann, E. Hüllermeier, & R. Mikut (Eds.), Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing (pp. 1–8). bibtex: '@inproceedings{Lu_Hüllermeier_2016, title={Support vector classification on noisy data using fuzzy supersets losses}, booktitle={Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing}, author={Lu, S. and Hüllermeier, Eyke}, editor={Hoffmann, F. and Hüllermeier, Eyke and Mikut, R.Editors}, year={2016}, pages={1–8} }' chicago: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data Using Fuzzy Supersets Losses.” In Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing, edited by F. Hoffmann, Eyke Hüllermeier, and R. Mikut, 1–8, 2016. ieee: S. Lu and E. Hüllermeier, “Support vector classification on noisy data using fuzzy supersets losses,” in Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing, 2016, pp. 1–8. mla: Lu, S., and Eyke Hüllermeier. “Support Vector Classification on Noisy Data Using Fuzzy Supersets Losses.” Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing, edited by F. Hoffmann et al., 2016, pp. 1–8. short: 'S. Lu, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing, 2016, pp. 1–8.' date_created: 2019-06-11T15:46:58Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: F. full_name: Hoffmann, F. last_name: Hoffmann - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier - first_name: R. full_name: Mikut, R. last_name: Mikut language: - iso: eng page: 1-8 publication: Proceedings 26. Workshop Computational Intelligence, KIT Scientific Publishing status: public title: Support vector classification on noisy data using fuzzy supersets losses type: conference user_id: '49109' year: '2016' ... --- _id: '10231' author: - first_name: Dirk full_name: Schäfer, Dirk last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In Workshop LWDA “Lernen, Wissen, Daten, Analysen.” ; 2016.' apa: Schäfer, D., & Hüllermeier, E. (2016). Plackett-Luce networks for dyad ranking. In In Workshop LWDA “Lernen, Wissen, Daten, Analysen.” bibtex: '@inproceedings{Schäfer_Hüllermeier_2016, title={Plackett-Luce networks for dyad ranking}, booktitle={In Workshop LWDA “Lernen, Wissen, Daten, Analysen”}, author={Schäfer, Dirk and Hüllermeier, Eyke}, year={2016} }' chicago: Schäfer, Dirk, and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.” In In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016. ieee: D. Schäfer and E. Hüllermeier, “Plackett-Luce networks for dyad ranking,” in In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016. mla: Schäfer, Dirk, and Eyke Hüllermeier. “Plackett-Luce Networks for Dyad Ranking.” In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016. short: 'D. Schäfer, E. Hüllermeier, in: In Workshop LWDA “Lernen, Wissen, Daten, Analysen,” 2016.' date_created: 2019-06-11T15:49:26Z date_updated: 2022-01-06T06:50:32Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng publication: In Workshop LWDA "Lernen, Wissen, Daten, Analysen" status: public title: Plackett-Luce networks for dyad ranking type: conference user_id: '49109' year: '2016' ... --- _id: '10263' citation: ama: 'Kaminka GA, Fox M, Bouquet P, et al., eds. ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence. Vol 285. The Hague, The Netherlands: IOS Press; 2016.' apa: 'Kaminka, G. A., Fox, M., Bouquet, P., Hüllermeier, E., Dignum, V., Dignum, F., & van Harmelen, F. (Eds.). (2016). ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence (Vol. 285). The Hague, The Netherlands: IOS Press.' bibtex: '@book{Kaminka_Fox_Bouquet_Hüllermeier_Dignum_Dignum_van Harmelen_2016, place={The Hague, The Netherlands}, series={Frontiers in Artificial Intelligence and Applications, The Hague, The Netherlands}, title={ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence}, volume={285}, publisher={IOS Press}, year={2016}, collection={Frontiers in Artificial Intelligence and Applications, The Hague, The Netherlands} }' chicago: 'Kaminka, G.A., M. Fox, P. Bouquet, Eyke Hüllermeier, V. Dignum, F. Dignum, and F. van Harmelen, eds. ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence. Vol. 285. Frontiers in Artificial Intelligence and Applications, The Hague, The Netherlands. The Hague, The Netherlands: IOS Press, 2016.' ieee: 'G. A. Kaminka et al., Eds., ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence, vol. 285. The Hague, The Netherlands: IOS Press, 2016.' mla: Kaminka, G. A., et al., editors. ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence. Vol. 285, IOS Press, 2016. short: G.A. Kaminka, M. Fox, P. Bouquet, E. Hüllermeier, V. Dignum, F. Dignum, F. van Harmelen, eds., ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence, IOS Press, The Hague, The Netherlands, 2016. date_created: 2019-06-18T15:07:10Z date_updated: 2022-01-06T06:50:33Z department: - _id: '34' - _id: '7' - _id: '355' editor: - first_name: G.A. full_name: Kaminka, G.A. last_name: Kaminka - first_name: M. full_name: Fox, M. last_name: Fox - first_name: P. full_name: Bouquet, P. last_name: Bouquet - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: V. full_name: Dignum, V. last_name: Dignum - first_name: F. full_name: Dignum, F. last_name: Dignum - first_name: F. full_name: van Harmelen, F. last_name: van Harmelen intvolume: ' 285' language: - iso: eng place: The Hague, The Netherlands publisher: IOS Press series_title: Frontiers in Artificial Intelligence and Applications, The Hague, The Netherlands status: public title: ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence type: conference_editor user_id: '49109' volume: 285 year: '2016' ... --- _id: '10264' author: - first_name: M. full_name: Leinweber, M. last_name: Leinweber - first_name: T. full_name: Fober, T. last_name: Fober - first_name: M. full_name: Strickert, M. last_name: Strickert - first_name: L. full_name: Baumgärtner, L. last_name: Baumgärtner - first_name: G. full_name: Klebe, G. last_name: Klebe - first_name: B. full_name: Freisleben, B. last_name: Freisleben - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Leinweber M, Fober T, Strickert M, et al. CavSimBase: A database for large scale comparison of protein binding sites. IEEE Transactions on Knowledge and Data Engineering. 2016;28(6):1423-1434.' apa: 'Leinweber, M., Fober, T., Strickert, M., Baumgärtner, L., Klebe, G., Freisleben, B., & Hüllermeier, E. (2016). CavSimBase: A database for large scale comparison of protein binding sites. IEEE Transactions on Knowledge and Data Engineering, 28(6), 1423–1434.' bibtex: '@article{Leinweber_Fober_Strickert_Baumgärtner_Klebe_Freisleben_Hüllermeier_2016, title={CavSimBase: A database for large scale comparison of protein binding sites}, volume={28}, number={6}, journal={IEEE Transactions on Knowledge and Data Engineering}, author={Leinweber, M. and Fober, T. and Strickert, M. and Baumgärtner, L. and Klebe, G. and Freisleben, B. and Hüllermeier, Eyke}, year={2016}, pages={1423–1434} }' chicago: 'Leinweber, M., T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, and Eyke Hüllermeier. “CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites.” IEEE Transactions on Knowledge and Data Engineering 28, no. 6 (2016): 1423–34.' ieee: 'M. Leinweber et al., “CavSimBase: A database for large scale comparison of protein binding sites,” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, pp. 1423–1434, 2016.' mla: 'Leinweber, M., et al. “CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites.” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, 2016, pp. 1423–34.' short: M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, E. Hüllermeier, IEEE Transactions on Knowledge and Data Engineering 28 (2016) 1423–1434. date_created: 2019-06-18T15:29:05Z date_updated: 2022-01-06T06:50:33Z department: - _id: '34' - _id: '7' - _id: '355' intvolume: ' 28' issue: '6' language: - iso: eng page: 1423-1434 publication: IEEE Transactions on Knowledge and Data Engineering status: public title: 'CavSimBase: A database for large scale comparison of protein binding sites' type: journal_article user_id: '49109' volume: 28 year: '2016' ... --- _id: '10266' author: - first_name: M. full_name: Riemenschneider, M. last_name: Riemenschneider - first_name: Robin full_name: Senge, Robin last_name: Senge - first_name: U. full_name: Neumann, U. last_name: Neumann - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier - first_name: D. full_name: Heider, D. last_name: Heider citation: ama: Riemenschneider M, Senge R, Neumann U, Hüllermeier E, Heider D. Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification. BioData Mining. 2016;9(10). apa: Riemenschneider, M., Senge, R., Neumann, U., Hüllermeier, E., & Heider, D. (2016). Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification. BioData Mining, 9(10). bibtex: '@article{Riemenschneider_Senge_Neumann_Hüllermeier_Heider_2016, title={Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification}, volume={9}, number={10}, journal={BioData Mining}, author={Riemenschneider, M. and Senge, Robin and Neumann, U. and Hüllermeier, Eyke and Heider, D.}, year={2016} }' chicago: Riemenschneider, M., Robin Senge, U. Neumann, Eyke Hüllermeier, and D. Heider. “Exploiting HIV-1 Protease and Reverse Transcriptase Cross-Resistance Information for Improved Drug Resistance Prediction by Means of Multi-Label Classification.” BioData Mining 9, no. 10 (2016). ieee: M. Riemenschneider, R. Senge, U. Neumann, E. Hüllermeier, and D. Heider, “Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification,” BioData Mining, vol. 9, no. 10, 2016. mla: Riemenschneider, M., et al. “Exploiting HIV-1 Protease and Reverse Transcriptase Cross-Resistance Information for Improved Drug Resistance Prediction by Means of Multi-Label Classification.” BioData Mining, vol. 9, no. 10, 2016. short: M. Riemenschneider, R. Senge, U. Neumann, E. Hüllermeier, D. Heider, BioData Mining 9 (2016). date_created: 2019-06-18T15:37:19Z date_updated: 2022-01-06T06:50:33Z department: - _id: '34' - _id: '7' - _id: '355' intvolume: ' 9' issue: '10' language: - iso: eng publication: BioData Mining status: public title: Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification type: journal_article user_id: '49109' volume: 9 year: '2016' ... --- _id: '280' abstract: - lang: eng text: The Collaborative Research Centre "On-The-Fly Computing" works on foundations and principles for the vision of the Future Internet. It proposes the paradigm of On-The-Fly Computing, which tackles emerging worldwide service markets. In these markets, service providers trade software, platform, and infrastructure as a service. Service requesters state requirements on services. To satisfy these requirements, the new role of brokers, who are (human) actors building service compositions on the fly, is introduced. Brokers have to specify service compositions formally and comprehensively using a domain-specific language (DSL), and to use service matching for the discovery of the constituent services available in the market. The broker's choice of the DSL and matching approaches influences her success of building compositions as distinctive properties of different service markets play a significant role. In this paper, we propose a new approach of engineering a situation-specific DSL by customizing a comprehensive, modular DSL and its matching for given service market properties. This enables the broker to create market-specific composition specifications and to perform market-specific service matching. As a result, the broker builds service compositions satisfying the requester's requirements more accurately. We evaluated the presented concepts using case studies in service markets for tourism and university management. author: - first_name: Svetlana full_name: Arifulina, Svetlana last_name: Arifulina - first_name: Marie Christin full_name: Platenius, Marie Christin last_name: Platenius - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels - first_name: Wilhelm full_name: Schäfer, Wilhelm last_name: Schäfer citation: ama: 'Arifulina S, Platenius MC, Mohr F, Engels G, Schäfer W. Market-Specific Service Compositions: Specification and Matching. In: Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet. ; 2015:333--340. doi:10.1109/SERVICES.2015.58' apa: 'Arifulina, S., Platenius, M. C., Mohr, F., Engels, G., & Schäfer, W. (2015). Market-Specific Service Compositions: Specification and Matching. In Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet (pp. 333--340). https://doi.org/10.1109/SERVICES.2015.58' bibtex: '@inproceedings{Arifulina_Platenius_Mohr_Engels_Schäfer_2015, title={Market-Specific Service Compositions: Specification and Matching}, DOI={10.1109/SERVICES.2015.58}, booktitle={Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet}, author={Arifulina, Svetlana and Platenius, Marie Christin and Mohr, Felix and Engels, Gregor and Schäfer, Wilhelm}, year={2015}, pages={333--340} }' chicago: 'Arifulina, Svetlana, Marie Christin Platenius, Felix Mohr, Gregor Engels, and Wilhelm Schäfer. “Market-Specific Service Compositions: Specification and Matching.” In Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 333--340, 2015. https://doi.org/10.1109/SERVICES.2015.58.' ieee: 'S. Arifulina, M. C. Platenius, F. Mohr, G. Engels, and W. Schäfer, “Market-Specific Service Compositions: Specification and Matching,” in Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340.' mla: 'Arifulina, Svetlana, et al. “Market-Specific Service Compositions: Specification and Matching.” Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340, doi:10.1109/SERVICES.2015.58.' short: 'S. Arifulina, M.C. Platenius, F. Mohr, G. Engels, W. Schäfer, in: Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340.' date_created: 2017-10-17T12:41:46Z date_updated: 2022-01-06T06:57:49Z ddc: - '040' department: - _id: '66' - _id: '76' - _id: '355' doi: 10.1109/SERVICES.2015.58 file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-21T09:26:04Z date_updated: 2018-03-21T09:26:04Z file_id: '1470' file_name: 280-07196546.pdf file_size: 234260 relation: main_file success: 1 file_date_updated: 2018-03-21T09:26:04Z has_accepted_license: '1' language: - iso: eng page: 333--340 project: - _id: '1' name: SFB 901 - _id: '9' name: SFB 901 - Subprojekt B1 - _id: '10' name: SFB 901 - Subproject B2 - _id: '3' name: SFB 901 - Project Area B publication: 'Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet' status: public title: 'Market-Specific Service Compositions: Specification and Matching' type: conference user_id: '477' year: '2015' ... --- _id: '323' abstract: - lang: eng text: On-the-fly composition of service-based software solutions is still a challenging task. Even more challenges emerge when facing automatic service composition in markets of composed services for end users. In this paper, we focus on the functional discrepancy between “what a user wants” specified in terms of a request and “what a user gets” when executing a composed service. To meet the challenge of functional discrepancy, we propose the combination of existing symbolic composition approaches with machine learning techniques. We developed a learning recommendation system that expands the capabilities of existing composition algorithms to facilitate adaptivity and consequently reduces functional discrepancy. As a representative of symbolic techniques, an Artificial Intelligence planning based approach produces solutions that are correct with respect to formal specifications. Our learning recommendation system supports the symbolic approach in decision-making. Reinforcement Learning techniques enable the recommendation system to adjust its recommendation strategy over time based on user ratings. We implemented the proposed functionality in terms of a prototypical composition framework. Preliminary results from experiments conducted in the image processing domain illustrate the benefit of combining both complementary techniques. author: - first_name: Alexander full_name: Jungmann, Alexander last_name: Jungmann - first_name: Felix full_name: Mohr, Felix last_name: Mohr citation: ama: Jungmann A, Mohr F. An approach towards adaptive service composition in markets of composed services. Journal of Internet Services and Applications. 2015;(1):1-18. doi:10.1186/s13174-015-0022-8 apa: Jungmann, A., & Mohr, F. (2015). An approach towards adaptive service composition in markets of composed services. Journal of Internet Services and Applications, (1), 1–18. https://doi.org/10.1186/s13174-015-0022-8 bibtex: '@article{Jungmann_Mohr_2015, title={An approach towards adaptive service composition in markets of composed services}, DOI={10.1186/s13174-015-0022-8}, number={1}, journal={Journal of Internet Services and Applications}, publisher={Springer}, author={Jungmann, Alexander and Mohr, Felix}, year={2015}, pages={1–18} }' chicago: 'Jungmann, Alexander, and Felix Mohr. “An Approach towards Adaptive Service Composition in Markets of Composed Services.” Journal of Internet Services and Applications, no. 1 (2015): 1–18. https://doi.org/10.1186/s13174-015-0022-8.' ieee: A. Jungmann and F. Mohr, “An approach towards adaptive service composition in markets of composed services,” Journal of Internet Services and Applications, no. 1, pp. 1–18, 2015. mla: Jungmann, Alexander, and Felix Mohr. “An Approach towards Adaptive Service Composition in Markets of Composed Services.” Journal of Internet Services and Applications, no. 1, Springer, 2015, pp. 1–18, doi:10.1186/s13174-015-0022-8. short: A. Jungmann, F. Mohr, Journal of Internet Services and Applications (2015) 1–18. date_created: 2017-10-17T12:41:55Z date_updated: 2022-01-06T06:59:06Z ddc: - '040' department: - _id: '355' doi: 10.1186/s13174-015-0022-8 file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-20T07:39:17Z date_updated: 2018-03-20T07:39:17Z file_id: '1429' file_name: 323-An_approach_towards_adaptive_service_composition_in_markets_of_composed_services.pdf file_size: 2842281 relation: main_file success: 1 file_date_updated: 2018-03-20T07:39:17Z has_accepted_license: '1' issue: '1' language: - iso: eng page: 1-18 project: - _id: '1' name: SFB 901 - _id: '10' name: SFB 901 - Subprojekt B2 - _id: '3' name: SFB 901 - Project Area B publication: Journal of Internet Services and Applications publisher: Springer status: public title: An approach towards adaptive service composition in markets of composed services type: journal_article user_id: '477' year: '2015' ... --- _id: '324' abstract: - lang: eng text: Services are self-contained software components that can beused platform independent and that aim at maximizing software reuse. Abasic concern in service oriented architectures is to measure the reusabilityof services. One of the most important qualities is the functionalreusability, which indicates how relevant the task is that a service solves.Current metrics for functional reusability of software, however, have verylittle explanatory power and do not accomplish this goal.This paper presents a new approach to estimate the functional reusabilityof services based on their relevance. To this end, it denes the degreeto which a service enables the execution of other services as its contri-bution. Based on the contribution, relevance of services is dened as anestimation for their functional reusability. Explanatory power is obtainedby normalizing relevance values with a reference service. The applicationof the metric to a service test set conrms its supposed capabilities. author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr citation: ama: 'Mohr F. A Metric for Functional Reusability of Services. In: Proceedings of the 14th International Conference on Software Reuse (ICSR). LNCS. ; 2015:298--313. doi:10.1007/978-3-319-14130-5_21' apa: Mohr, F. (2015). A Metric for Functional Reusability of Services. In Proceedings of the 14th International Conference on Software Reuse (ICSR) (pp. 298--313). https://doi.org/10.1007/978-3-319-14130-5_21 bibtex: '@inproceedings{Mohr_2015, series={LNCS}, title={A Metric for Functional Reusability of Services}, DOI={10.1007/978-3-319-14130-5_21}, booktitle={Proceedings of the 14th International Conference on Software Reuse (ICSR)}, author={Mohr, Felix}, year={2015}, pages={298--313}, collection={LNCS} }' chicago: Mohr, Felix. “A Metric for Functional Reusability of Services.” In Proceedings of the 14th International Conference on Software Reuse (ICSR), 298--313. LNCS, 2015. https://doi.org/10.1007/978-3-319-14130-5_21. ieee: F. Mohr, “A Metric for Functional Reusability of Services,” in Proceedings of the 14th International Conference on Software Reuse (ICSR), 2015, pp. 298--313. mla: Mohr, Felix. “A Metric for Functional Reusability of Services.” Proceedings of the 14th International Conference on Software Reuse (ICSR), 2015, pp. 298--313, doi:10.1007/978-3-319-14130-5_21. short: 'F. Mohr, in: Proceedings of the 14th International Conference on Software Reuse (ICSR), 2015, pp. 298--313.' date_created: 2017-10-17T12:41:55Z date_updated: 2022-01-06T06:59:07Z ddc: - '040' department: - _id: '355' doi: 10.1007/978-3-319-14130-5_21 file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-20T07:38:44Z date_updated: 2018-03-20T07:38:44Z file_id: '1428' file_name: 324-ICSR-Mohr-15.pdf file_size: 569475 relation: main_file success: 1 file_date_updated: 2018-03-20T07:38:44Z has_accepted_license: '1' language: - iso: eng page: 298--313 project: - _id: '1' name: SFB 901 - _id: '10' name: SFB 901 - Subprojekt B2 - _id: '3' name: SFB 901 - Project Area B publication: Proceedings of the 14th International Conference on Software Reuse (ICSR) series_title: LNCS status: public title: A Metric for Functional Reusability of Services type: conference user_id: '477' year: '2015' ... --- _id: '319' abstract: - lang: eng text: Services are self-contained and platform independent software components that aim at maximizing software reuse. The automated composition of services to a target software artifact has been tackled with many AI techniques, but existing approaches make unreasonably strong assumptions such as a predefined data flow, are limited to tiny problem sizes, ignore non-functional properties, or assume offline service repositories. This paper presents an algorithm that automatically composes services without making such assumptions. We employ a backward search algorithm that starts from an empty composition and prepends service calls to already discovered candidates until a solution is found. Available services are determined during the search process. We implemented our algorithm, performed an experimental evaluation, and compared it to other approaches. author: - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Alexander full_name: Jungmann, Alexander last_name: Jungmann - first_name: Hans full_name: Kleine Büning, Hans last_name: Kleine Büning citation: ama: 'Mohr F, Jungmann A, Kleine Büning H. Automated Online Service Composition. In: Proceedings of the 12th IEEE International Conference on Services Computing (SCC). ; 2015:57--64. doi:10.1109/SCC.2015.18' apa: Mohr, F., Jungmann, A., & Kleine Büning, H. (2015). Automated Online Service Composition. In Proceedings of the 12th IEEE International Conference on Services Computing (SCC) (pp. 57--64). https://doi.org/10.1109/SCC.2015.18 bibtex: '@inproceedings{Mohr_Jungmann_Kleine Büning_2015, title={Automated Online Service Composition}, DOI={10.1109/SCC.2015.18}, booktitle={Proceedings of the 12th IEEE International Conference on Services Computing (SCC)}, author={Mohr, Felix and Jungmann, Alexander and Kleine Büning, Hans}, year={2015}, pages={57--64} }' chicago: Mohr, Felix, Alexander Jungmann, and Hans Kleine Büning. “Automated Online Service Composition.” In Proceedings of the 12th IEEE International Conference on Services Computing (SCC), 57--64, 2015. https://doi.org/10.1109/SCC.2015.18. ieee: F. Mohr, A. Jungmann, and H. Kleine Büning, “Automated Online Service Composition,” in Proceedings of the 12th IEEE International Conference on Services Computing (SCC), 2015, pp. 57--64. mla: Mohr, Felix, et al. “Automated Online Service Composition.” Proceedings of the 12th IEEE International Conference on Services Computing (SCC), 2015, pp. 57--64, doi:10.1109/SCC.2015.18. short: 'F. Mohr, A. Jungmann, H. Kleine Büning, in: Proceedings of the 12th IEEE International Conference on Services Computing (SCC), 2015, pp. 57--64.' date_created: 2017-10-17T12:41:54Z date_updated: 2022-01-06T06:59:04Z ddc: - '040' department: - _id: '355' doi: 10.1109/SCC.2015.18 file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-20T07:42:03Z date_updated: 2018-03-20T07:42:03Z file_id: '1434' file_name: 319-07207336.pdf file_size: 345742 relation: main_file success: 1 file_date_updated: 2018-03-20T07:42:03Z has_accepted_license: '1' language: - iso: eng page: 57--64 project: - _id: '1' name: SFB 901 - _id: '10' name: SFB 901 - Subprojekt B2 - _id: '3' name: SFB 901 - Project Area B publication: Proceedings of the 12th IEEE International Conference on Services Computing (SCC) status: public title: Automated Online Service Composition type: conference user_id: '477' year: '2015' ... --- _id: '4792' author: - first_name: Robin full_name: Senge, Robin last_name: Senge - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: Senge R, Hüllermeier E. Fast Fuzzy Pattern Tree Learning for Classification. IEEE Transactions on Fuzzy Systems. 2015;23(6):2024-2033. doi:10.1109/tfuzz.2015.2396078 apa: Senge, R., & Hüllermeier, E. (2015). Fast Fuzzy Pattern Tree Learning for Classification. IEEE Transactions on Fuzzy Systems, 23(6), 2024–2033. https://doi.org/10.1109/tfuzz.2015.2396078 bibtex: '@article{Senge_Hüllermeier_2015, title={Fast Fuzzy Pattern Tree Learning for Classification}, volume={23}, DOI={10.1109/tfuzz.2015.2396078}, number={6}, journal={IEEE Transactions on Fuzzy Systems}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Senge, Robin and Hüllermeier, Eyke}, year={2015}, pages={2024–2033} }' chicago: 'Senge, Robin, and Eyke Hüllermeier. “Fast Fuzzy Pattern Tree Learning for Classification.” IEEE Transactions on Fuzzy Systems 23, no. 6 (2015): 2024–33. https://doi.org/10.1109/tfuzz.2015.2396078.' ieee: R. Senge and E. Hüllermeier, “Fast Fuzzy Pattern Tree Learning for Classification,” IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, pp. 2024–2033, 2015. mla: Senge, Robin, and Eyke Hüllermeier. “Fast Fuzzy Pattern Tree Learning for Classification.” IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, Institute of Electrical and Electronics Engineers (IEEE), 2015, pp. 2024–33, doi:10.1109/tfuzz.2015.2396078. short: R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033. date_created: 2018-10-22T06:53:37Z date_updated: 2022-01-06T07:01:22Z ddc: - '000' department: - _id: '355' doi: 10.1109/tfuzz.2015.2396078 file: - access_level: closed content_type: application/pdf creator: ups date_created: 2018-11-02T15:53:23Z date_updated: 2018-11-02T15:53:23Z file_id: '5316' file_name: 07018950.pdf file_size: 732827 relation: main_file success: 1 file_date_updated: 2018-11-02T15:53:23Z has_accepted_license: '1' intvolume: ' 23' issue: '6' language: - iso: eng page: 2024-2033 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '11' name: SFB 901 - Subproject B3 publication: IEEE Transactions on Fuzzy Systems publication_identifier: issn: - 1063-6706 - 1941-0034 publication_status: published publisher: Institute of Electrical and Electronics Engineers (IEEE) status: public title: Fast Fuzzy Pattern Tree Learning for Classification type: journal_article user_id: '49109' volume: 23 year: '2015' ... --- _id: '15406' author: - first_name: D. full_name: Schäfer, D. last_name: Schäfer - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Schäfer D, Hüllermeier E. Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations. In: In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located ECML/PKDD, Porto, Portugal. ; 2015:110-111.' apa: 'Schäfer, D., & Hüllermeier, E. (2015). Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations. In in Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located ECML/PKDD, Porto, Portugal (pp. 110–111).' bibtex: '@inproceedings{Schäfer_Hüllermeier_2015, title={Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations}, booktitle={in Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located ECML/PKDD, Porto, Portugal}, author={Schäfer, D. and Hüllermeier, Eyke}, year={2015}, pages={110–111} }' chicago: 'Schäfer, D., and Eyke Hüllermeier. “Preference-Based Meta-Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations.” In In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located ECML/PKDD, Porto, Portugal, 110–11, 2015.' ieee: 'D. Schäfer and E. Hüllermeier, “Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations,” in in Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located ECML/PKDD, Porto, Portugal, 2015, pp. 110–111.' mla: 'Schäfer, D., and Eyke Hüllermeier. “Preference-Based Meta-Learning Using Dyad Ranking: Recommending Algorithms in Cold-Start Situations.” In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located ECML/PKDD, Porto, Portugal, 2015, pp. 110–11.' short: 'D. Schäfer, E. Hüllermeier, in: In Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection Co-Located ECML/PKDD, Porto, Portugal, 2015, pp. 110–111.' date_created: 2019-12-19T16:52:09Z date_updated: 2022-01-06T06:52:23Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 110-111 publication: in Proceedings of the 2015 international Workshop on Meta-Learning and Algorithm Selection co-located ECML/PKDD, Porto, Portugal status: public title: 'Preference-based meta-learning using dyad ranking: Recommending algorithms in cold-start situations' type: conference user_id: '49109' year: '2015' ... --- _id: '15749' author: - first_name: Adil full_name: Paul, Adil last_name: Paul - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Paul A, Hüllermeier E. A cbr approach to the angry birds game. In: In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany. ; 2015:68-77.' apa: Paul, A., & Hüllermeier, E. (2015). A cbr approach to the angry birds game. In In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany (pp. 68–77). bibtex: '@inproceedings{Paul_Hüllermeier_2015, title={A cbr approach to the angry birds game}, booktitle={In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany}, author={Paul, Adil and Hüllermeier, Eyke}, year={2015}, pages={68–77} }' chicago: Paul, Adil, and Eyke Hüllermeier. “A Cbr Approach to the Angry Birds Game.” In In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany, 68–77, 2015. ieee: A. Paul and E. Hüllermeier, “A cbr approach to the angry birds game,” in In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany, 2015, pp. 68–77. mla: Paul, Adil, and Eyke Hüllermeier. “A Cbr Approach to the Angry Birds Game.” In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany, 2015, pp. 68–77. short: 'A. Paul, E. Hüllermeier, in: In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany, 2015, pp. 68–77.' date_created: 2020-02-03T14:07:45Z date_updated: 2022-01-06T06:52:32Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng page: 68-77 publication: In Workshop Proceedings from ICCBR, 23rd International Conference on Case-Based Reasoning, Frankfurt, Germany status: public title: A cbr approach to the angry birds game type: conference user_id: '49109' year: '2015' ...