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418 Publications


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 | 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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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: 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 | 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.
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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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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 | 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. 2020.
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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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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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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 | 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 | 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 | Preprint | LibreCat-ID: 19523
Pfannschmidt, Karlson, et al. “Learning Choice Functions: Concepts and Architectures.” ArXiv:1901.10860, 2019.
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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.
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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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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: 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 | 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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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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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 | 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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2019 | Preprint | LibreCat-ID: 18016
Bengs, Viktor, and Eyke Hüllermeier. “Preselection Bandits under the Plackett-Luce Model.” ArXiv:1907.06123.
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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.
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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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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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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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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 | 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, MIT Press Journals, doi:10.1162/evco_a_00266.
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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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2018 | Conference Paper | LibreCat-ID: 10184
Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” Proc. 21st Int. Conference on Discovery Science (DS), 2018, pp. 161–75.
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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 | 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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2018 | Conference (Editor) | LibreCat-ID: 10591
Abiteboul, S., et al., editors. Research Directions for Principles of Data Management. Vol. 7, no. 1, 2018, pp. 1–29.
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2018 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. 2018.
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2018 | Preprint | LibreCat-ID: 17713
Wever, Marcel Dominik, et al. Automated Multi-Label Classification Based on ML-Plan. Arxiv, 2018.
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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: 10148
El Mesaoudi-Paul, Adil, et al. “Ranking Distributions Based on  Noisy Sorting.” Proc. 35th Int. Conference on Machine Learning (ICML), 2018, pp. 3469–77.
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2018 | Conference Paper | LibreCat-ID: 10181
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.
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2018 | Journal Article | LibreCat-ID: 16038
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.
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2018 | Conference Paper | LibreCat-ID: 2109
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.
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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 | Book Chapter | LibreCat-ID: 6423
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.
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2018 | Preprint | LibreCat-ID: 17714
Mohr, Felix, et al. Automated Machine Learning Service Composition. 2018.
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2018 | Journal Article | LibreCat-ID: 10276
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.
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2018 | Conference Paper | LibreCat-ID: 10149
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.
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2018 | Book Chapter | LibreCat-ID: 10783
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.
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