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449 Publications
2020 | Preprint | LibreCat-ID: 17605 |
Heid, Stefan Helmut, Marcel Dominik Wever, and Eyke Hüllermeier. “Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction.” Journal of Data Mining and Digital Humanities. episciences, n.d.
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2020 | Conference Paper | LibreCat-ID: 20306
Tornede, Alexander, Marcel Dominik Wever, and Eyke Hüllermeier. “Towards Meta-Algorithm Selection.” In Workshop MetaLearn 2020 @ NeurIPS 2020, 2020.
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2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul, Adil, Dimitri Weiß, Viktor Bengs, Eyke Hüllermeier, and Kevin Tierney. “Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach.” In Learning and Intelligent Optimization. LION 2020., 12096:216–32. Lecture Notes in Computer Science. Cham: Springer, 2020. https://doi.org/10.1007/978-3-030-53552-0_22.
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2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul, Adil, Viktor Bengs, and Eyke Hüllermeier. “Online Preselection with Context Information under the Plackett-Luce Model.” ArXiv:2002.04275, n.d.
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2020 | Conference Paper | LibreCat-ID: 18276
Tornede, Alexander, Marcel Dominik Wever, Stefan Werner, Felix Mohr, and Eyke Hüllermeier. “Run2Survive: A Decision-Theoretic Approach to Algorithm Selection Based on Survival Analysis.” In ACML 2020, 2020.
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2020 | Journal Article | LibreCat-ID: 16725
Richter, Cedric, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim. “Algorithm Selection for Software Validation Based on Graph Kernels.” Journal of Automated Software Engineering, n.d.
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2020 | Conference Paper | LibreCat-ID: 15629
Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification.” Springer, n.d.
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2020 | Journal Article | LibreCat-ID: 15025
Wever, Marcel Dominik, Lorijn van Rooijen, and Heiko Hamann. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation 28, no. 2 (2020): 165–193. https://doi.org/10.1162/evco_a_00266.
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2019 | Preprint | LibreCat-ID: 19523
Pfannschmidt, Karlson, Pritha Gupta, and Eyke Hüllermeier. “Learning Choice Functions: Concepts and Architectures.” ArXiv:1901.10860, 2019.
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2019 | Journal Article | LibreCat-ID: 17565
Merten, Marie-Luis, Nina Seemann, and Marcel Dominik Wever. “Grammatikwandel digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff.” Niederdeutsches Jahrbuch, no. 142 (2019): 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, Felix Mohr, Eyke Hüllermeier, and Alexander Hetzer. “Towards Automated Machine Learning for Multi-Label Classification,” 2019.
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2019 | Journal Article | LibreCat-ID: 10578
Tagne, V. K., S. Fotso, L. A. Fono, and Eyke Hüllermeier. “Choice Functions Generated by Mallows and Plackett–Luce Relations.” New Mathematics and Natural Computation 15, no. 2 (2019): 191–213.
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2019 | Journal Article | LibreCat-ID: 15001
Couso, Ines, Christian Borgelt, Eyke Hüllermeier, and Rudolf Kruse. “Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning.” IEEE Computational Intelligence Magazine, 2019, 31–44. https://doi.org/10.1109/mci.2018.2881642.
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2019 | Journal Article | LibreCat-ID: 15002 |
Waegeman, Willem, Krzysztof Dembczynski, and Eyke Hüllermeier. “Multi-Target Prediction: A Unifying View on Problems and Methods.” Data Mining and Knowledge Discovery 33, no. 2 (2019): 293–324. https://doi.org/10.1007/s10618-018-0595-5.
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2019 | Conference Paper | LibreCat-ID: 15003
Mortier, Thomas, Marek Wydmuch, Krzysztof Dembczynski, Eyke Hüllermeier, and Willem Waegeman. “Set-Valued Prediction in Multi-Class Classification.” In 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 | Book Chapter | LibreCat-ID: 15004
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Feature Selection for Analogy-Based Learning to Rank.” In Discovery Science. Cham, 2019. https://doi.org/10.1007/978-3-030-33778-0_22.
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2019 | Book Chapter | LibreCat-ID: 15005
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Analogy-Based Preference Learning with Kernels.” In KI 2019: Advances in Artificial Intelligence. Cham, 2019. https://doi.org/10.1007/978-3-030-30179-8_3.
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2019 | Book Chapter | LibreCat-ID: 15006
Nguyen, Vu-Linh, Sébastien Destercke, and Eyke Hüllermeier. “Epistemic Uncertainty Sampling.” In Discovery Science. Cham, 2019. https://doi.org/10.1007/978-3-030-33778-0_7.
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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.” In Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101), 2019. https://doi.org/10.1016/j.jmva.2019.02.017.
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2019 | Conference Paper | LibreCat-ID: 15009
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.
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2019 | Conference Paper | LibreCat-ID: 15011 |
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.
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2019 | Conference Paper | LibreCat-ID: 15013
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.
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2019 | Conference Paper | LibreCat-ID: 15014
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.
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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, 1–36. https://doi.org/10.1145/3363572.
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2019 | Journal Article | LibreCat-ID: 14027
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.
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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, 1523–79. https://doi.org/10.1214/19-ejs1555.
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2019 | Conference Abstract | LibreCat-ID: 13132
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.
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2019 | Conference Paper | LibreCat-ID: 10232 |
Wever, Marcel Dominik, Felix Mohr, Alexander Tornede, and Eyke Hüllermeier. “Automating Multi-Label Classification Extending ML-Plan,” 2019.
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2019 | Journal Article | LibreCat-ID: 20243
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.
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2018 | Conference Paper | LibreCat-ID: 2479 |
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.
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2018 | Preprint | LibreCat-ID: 19524
Pfannschmidt, Karlson, Pritha Gupta, and Eyke Hüllermeier. “Deep Architectures for Learning Context-Dependent Ranking Functions.” ArXiv:1803.05796, 2018.
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2018 | Conference Paper | LibreCat-ID: 2857 |
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.
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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 64, no. 6 (2018): 2614–20.
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2018 | Journal Article | LibreCat-ID: 24151
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.
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2018 | Conference Paper | LibreCat-ID: 2471 |
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.
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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. https://doi.org/10.1007/s10994-018-5733-1.
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2018 | Journal Article | LibreCat-ID: 3510 |
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.
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2018 | Conference Paper | LibreCat-ID: 3552 |
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.
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2018 | Conference Paper | LibreCat-ID: 3852 |
Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “ML-Plan for Unlimited-Length Machine Learning Pipelines.” In ICML 2018 AutoML Workshop, 2018.
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2018 | Conference Paper | LibreCat-ID: 2109 |
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.
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2018 | Preprint | LibreCat-ID: 17713 |
Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automated Multi-Label Classification Based on ML-Plan.” Arxiv, 2018.
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2018 | Preprint | LibreCat-ID: 17714 |
Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Automated Machine Learning Service Composition,” 2018.
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2018 | Bachelorsthesis | LibreCat-ID: 5693
Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018.
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2018 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. Universität Paderborn, 2018.
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2018 | Book Chapter | LibreCat-ID: 6423
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.
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2018 | Conference (Editor) | LibreCat-ID: 10591
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.
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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.” In Frontiers in Computational Intelligence, edited by Sanaz Mostaghim, Andreas Nürnberger, and Christian Borgelt, 31–46. Springer, 2018.
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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 107, no. 5 (2018): 903–41.
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2018 | Conference Paper | LibreCat-ID: 10145
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.
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