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449 Publications
2021 | Conference Paper | LibreCat-ID: 27381
Damke, Clemens, and Eyke Hüllermeier. “Ranking Structured Objects with Graph Neural Networks.” Proceedings of The 24th International Conference on Discovery Science (DS 2021), edited by Carlos Soares and Luis Torgo, vol. 12986, Springer, 2021, pp. 166–80, doi:10.1007/978-3-030-88942-5.
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| DOI
| arXiv
2021 | Dissertation | LibreCat-ID: 27284 | 
Wever, Marcel Dominik. Automated Machine Learning for Multi-Label Classification. 2021, doi:10.17619/UNIPB/1-1302.
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| DOI
2021 | Conference Paper | LibreCat-ID: 21198
Hanselle, Jonas Manuel, et al. Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. 2021.
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2020 | Book Chapter | LibreCat-ID: 19521
Pfannschmidt, Karlson, and Eyke Hüllermeier. “Learning Choice Functions via Pareto-Embeddings.” Lecture Notes in Computer Science, 2020, doi:10.1007/978-3-030-58285-2_30.
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| DOI
2020 | Conference Paper | LibreCat-ID: 19953 |
Damke, Clemens, et al. “A Novel Higher-Order Weisfeiler-Lehman Graph Convolution.” Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020), edited by Sinno Jialin Pan and Masashi Sugiyama, vol. 129, PMLR, 2020, pp. 49–64.
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| arXiv
2020 | Conference Paper | LibreCat-ID: 21534
Bengs, Viktor, and Eyke Hüllermeier. “Preselection Bandits.” International Conference on Machine Learning, 2020, pp. 778–87.
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2020 | Preprint | LibreCat-ID: 21536
Bengs, Viktor, and Eyke Hüllermeier. “Multi-Armed Bandits with Censored Consumption of Resources.” ArXiv:2011.00813, 2020.
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2020 | Conference Paper | LibreCat-ID: 17407
Tornede, Alexander, et al. “Extreme Algorithm Selection with Dyadic Feature Representation.” Discovery Science, 2020.
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2020 | Conference Paper | LibreCat-ID: 17408
Hanselle, Jonas Manuel, et al. “Hybrid Ranking and Regression for Algorithm Selection.” KI 2020: Advances in Artificial Intelligence, 2020.
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2020 | Conference Paper | LibreCat-ID: 17424
Tornede, Tanja, et al. “AutoML for Predictive Maintenance: One Tool to RUL Them All.” Proceedings of the ECMLPKDD 2020, 2020, doi:10.1007/978-3-030-66770-2_8.
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| DOI
2020 | Preprint | LibreCat-ID: 17605 |
Heid, Stefan Helmut, et al. “Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction.” Journal of Data Mining and Digital Humanities, episciences.
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2020 | Conference Paper | LibreCat-ID: 20306
Tornede, Alexander, et al. “Towards Meta-Algorithm Selection.” Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
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2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul, Adil, et al. “Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach.” Learning and Intelligent Optimization. LION 2020., vol. 12096, Springer, 2020, pp. 216–32, doi:10.1007/978-3-030-53552-0_22.
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| DOI
2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul, Adil, et al. “Online Preselection with Context Information under the Plackett-Luce Model.” ArXiv:2002.04275.
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2020 | Conference Paper | LibreCat-ID: 18276
Tornede, Alexander, et al. “Run2Survive: A Decision-Theoretic Approach to Algorithm Selection Based on Survival Analysis.” ACML 2020, 2020.
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2020 | Journal Article | LibreCat-ID: 16725
Richter, Cedric, et al. “Algorithm Selection for Software Validation Based on Graph Kernels.” Journal of Automated Software Engineering, Springer.
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2020 | Conference Paper | LibreCat-ID: 15629
Wever, Marcel Dominik, et al. LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification. Springer.
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2020 | Journal Article | LibreCat-ID: 15025
Wever, Marcel Dominik, et al. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation, vol. 28, no. 2, MIT Press Journals, 2020, pp. 165–193, doi:10.1162/evco_a_00266.
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2019 | Preprint | LibreCat-ID: 19523
Pfannschmidt, Karlson, et al. “Learning Choice Functions: Concepts and Architectures.” ArXiv:1901.10860, 2019.
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2019 | Journal Article | LibreCat-ID: 17565
Merten, Marie-Luis, et al. “Grammatikwandel digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff.” Niederdeutsches Jahrbuch, no. 142, 2019, pp. 124–46.
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2019 | Preprint | LibreCat-ID: 18018
Bengs, Viktor, and Hajo Holzmann. “Uniform Approximation in Classical Weak Convergence Theory.” ArXiv:1903.09864, 2019.
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2019 | Conference Abstract | LibreCat-ID: 8868
Wever, Marcel Dominik, et al. Towards Automated Machine Learning for Multi-Label Classification. 2019.
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2019 | Journal Article | LibreCat-ID: 10578
Tagne, V. K., et al. “Choice Functions Generated by Mallows and Plackett–Luce Relations.” New Mathematics and Natural Computation, vol. 15, no. 2, 2019, pp. 191–213.
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2019 | Journal Article | LibreCat-ID: 15001
Couso, Ines, et al. “Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning.” IEEE Computational Intelligence Magazine, 2019, pp. 31–44, doi:10.1109/mci.2018.2881642.
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| DOI
2019 | Journal Article | LibreCat-ID: 15002 |
Waegeman, Willem, et al. “Multi-Target Prediction: A Unifying View on Problems and Methods.” Data Mining and Knowledge Discovery, vol. 33, no. 2, 2019, pp. 293–324, doi:10.1007/s10618-018-0595-5.
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| DOI
2019 | Conference Paper | LibreCat-ID: 15003
Mortier, Thomas, et al. “Set-Valued Prediction in Multi-Class Classification.” Proceedings of the 31st Benelux Conference on Artificial Intelligence {(BNAIC} 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019, 2019.
LibreCat
2019 | Book Chapter | LibreCat-ID: 15004
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Feature Selection for Analogy-Based Learning to Rank.” Discovery Science, 2019, doi:10.1007/978-3-030-33778-0_22.
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| DOI
2019 | Book Chapter | LibreCat-ID: 15005
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Analogy-Based Preference Learning with Kernels.” KI 2019: Advances in Artificial Intelligence, 2019, doi:10.1007/978-3-030-30179-8_3.
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| DOI
2019 | Book Chapter | LibreCat-ID: 15006
Nguyen, Vu-Linh, et al. “Epistemic Uncertainty Sampling.” Discovery Science, 2019, doi:10.1007/978-3-030-33778-0_7.
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| DOI
2019 | Conference Paper | LibreCat-ID: 15007 |
Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA.” Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101), 2019, doi:10.1016/j.jmva.2019.02.017.
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2019 | Conference Paper | LibreCat-ID: 15009
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.
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| DOI
2019 | Conference Paper | LibreCat-ID: 15011 |
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.
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2019 | Conference Paper | LibreCat-ID: 15013
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.
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2019 | Conference Paper | LibreCat-ID: 15014
Hüllermeier, Eyke, et al. “Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants.” Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.
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2019 | Journal Article | LibreCat-ID: 15015
Henzgen, Sascha, and Eyke Hüllermeier. “Mining Rank Data.” ACM Transactions on Knowledge Discovery from Data, 2019, pp. 1–36, doi:10.1145/3363572.
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| DOI
2019 | Journal Article | LibreCat-ID: 14027
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.
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| DOI
2019 | Journal Article | LibreCat-ID: 14028
Bengs, Viktor, and Hajo Holzmann. “Adaptive Confidence Sets for Kink Estimation.” Electronic Journal of Statistics, 2019, pp. 1523–79, doi:10.1214/19-ejs1555.
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| DOI
2019 | Conference Abstract | LibreCat-ID: 13132
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.
LibreCat
2019 | Conference Paper | LibreCat-ID: 10232 |
Wever, Marcel Dominik, et al. Automating Multi-Label Classification Extending ML-Plan. 2019.
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2019 | Journal Article | LibreCat-ID: 20243
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.
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| DOI
2018 | Conference Paper | LibreCat-ID: 2479 |
Mohr, Felix, et al. “(WIP) Towards the Automated Composition of Machine Learning Services.” SCC, IEEE, 2018, doi:10.1109/SCC.2018.00039.
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2018 | Preprint | LibreCat-ID: 19524
Pfannschmidt, Karlson, et al. “Deep Architectures for Learning Context-Dependent Ranking Functions.” ArXiv:1803.05796, 2018.
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2018 | Conference Paper | LibreCat-ID: 2857 |
Mohr, Felix, et al. “Programmatic Task Network Planning.” Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.
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2018 | Journal Article | LibreCat-ID: 24150
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.
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2018 | Journal Article | LibreCat-ID: 24151
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.
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2018 | Conference Paper | LibreCat-ID: 2471 |
Mohr, Felix, et al. “On-The-Fly Service Construction with Prototypes.” SCC, IEEE Computer Society, 2018, doi:10.1109/SCC.2018.00036.
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2018 | Journal Article | LibreCat-ID: 3402
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.
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2018 | Journal Article | LibreCat-ID: 3510 |
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.
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2018 | Conference Paper | LibreCat-ID: 3552 |
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.
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2018 | Conference Paper | LibreCat-ID: 3852 |
Wever, Marcel Dominik, et al. “ML-Plan for Unlimited-Length Machine Learning Pipelines.” ICML 2018 AutoML Workshop, 2018.
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