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124 Publications


2019 | Conference Paper | LibreCat-ID: 10232
Wever MD, Mohr F, Tornede A, Hüllermeier E. Automating Multi-Label Classification Extending ML-Plan. In: ; 2019.
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2019 | Conference Abstract | LibreCat-ID: 8956
Hetzer A, Wever MD, Mohr F, Hüllermeier E. Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking. In: ; 2019.
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2019 | Conference Abstract | LibreCat-ID: 8868
Wever MD, Mohr F, Hüllermeier E, Hetzer A. Towards Automated Machine Learning for Multi-Label Classification. In: ; 2019.
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2018 | Conference Paper | LibreCat-ID: 10184
Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Proc. 21st Int. Conference on Discovery Science (DS). ; 2018:161-175.
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2018 | Conference Paper | LibreCat-ID: 3852
Wever MD, Mohr F, Hüllermeier E. ML-Plan for Unlimited-Length Machine Learning Pipelines. In: ICML 2018 AutoML Workshop. ; 2018.
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2018 | Conference Paper | LibreCat-ID: 2479
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
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2018 | Conference Paper | LibreCat-ID: 10153
Mohr F, Wever MD, Hüllermeier E. Reduction Stumps for Multi-class Classification. In: Proc. 17th Int. Symposium on Intelligent Data Analysis (IDA). ; 2018:225-237.
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2018 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl M. Learning about Learning Curves from Dataset Properties.; 2018.
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2018 | Conference Paper | LibreCat-ID: 10185
Seemann N, Geierhos M, Merten M-L, Tophinke D, Wever MD, Hüllermeier E. Supporting the Cognitive Process in Annotation Tasks. In: Postersession Computerlinguistik Der 40. Jahrestagung Der Deutschen Gesellschaft Für Sprachwissenschaft. ; 2018.
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2018 | Conference Paper | LibreCat-ID: 10154
Mohr F, Wever MD, Hüllermeier E, Faez A. (WIP) Towards the Automated Composition of Machine Learning Services. In: Proc. 15th Int. Conference on Services Computing (SCC). ; 2018:241-244.
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2018 | Conference Paper | LibreCat-ID: 10192
Wever MD, Mohr F, Hüllermeier E. ML-Plan for Unlimited-Length Machine Learning Pipelines. In: Int. Workshop on Automatic Machine Learning (AutoML) at ICML 2018. ; 2018.
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2018 | Journal Article | LibreCat-ID: 10274
Melnikov V, Hüllermeier E. On the effectiveness of heuristics for learning nested dichotomies: an empirial analysis. Machine Learning. 2018;107(8-10):1537-1560.
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2018 | Conference (Editor) | LibreCat-ID: 10591
Abiteboul S, Arenas M, Barceló P, et al., eds. Research Directions for Principles of Data Management. Vol 7.; 2018:1-29.
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2018 | Conference Paper | LibreCat-ID: 10181
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.
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2018 | Conference Paper | LibreCat-ID: 2109
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
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2018 | Conference Paper | LibreCat-ID: 2471
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
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2018 | Book Chapter | LibreCat-ID: 6423
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
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2018 | Conference Paper | LibreCat-ID: 10148
El Mesaoudi-Paul A, Hüllermeier E, Busa-Fekete R. Ranking Distributions based on  Noisy Sorting. In: Proc. 35th Int. Conference on Machine Learning (ICML). ; 2018:3469-3477.
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2018 | Conference Paper | LibreCat-ID: 3552
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
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2018 | Conference Paper | LibreCat-ID: 2857
Mohr F, Lettmann T, Hüllermeier E, Wever MD. Programmatic Task Network Planning. In: Proceedings of the 28th International Conference on Automated Planning and Scheduling. AAAI; 2018.
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2018 | Conference Paper | LibreCat-ID: 10149
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.
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2018 | Journal Article | LibreCat-ID: 10276
Schäfer D, Hüllermeier E. Dyad Ranking Using Plackett-Luce Models based on joint feature representations. Machine Learning. 2018;107(5):903-941.
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2018 | Journal Article | LibreCat-ID: 3402
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
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2018 | Bachelorsthesis | LibreCat-ID: 5693
Graf H. Ranking of Classification Algorithms in AutoML.; 2018.
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2018 | Journal Article | LibreCat-ID: 3510
Mohr F, Wever MD, Hüllermeier E. ML-Plan: Automated Machine Learning via Hierarchical Planning. Machine Learning. 2018. doi:10.1007/s10994-018-5735-z
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2018 | Conference Abstract | LibreCat-ID: 1379
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.
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2018 | Conference Paper | LibreCat-ID: 10152
Mohr F, Wever MD, Hüllermeier E. On-the-Fly Service Construction with Prototypes. In: Proc. 15th Int. Conference on Services Computing (SCC). ; 2018:225-232.
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2018 | Conference Paper | LibreCat-ID: 10188
Wever MD, Mohr F, Hüllermeier E. Ensembles of evolved nested dichotomies for classificaton. In: Proc. Genetic and Evolutionary Computation Conference (GECCO). ; 2018:561-568.
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2018 | Conference Paper | LibreCat-ID: 10145
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.
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2017 | Bachelorsthesis | LibreCat-ID: 5694
Schnitker NN. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies.; 2017.
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2017 | Conference Paper | LibreCat-ID: 1180
Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization. In: 27th Workshop Computational Intelligence. Dortmund; 2017.
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2017 | Conference Paper | LibreCat-ID: 10204
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.
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2017 | Conference Paper | LibreCat-ID: 10216
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.
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2017 | Conference Paper | LibreCat-ID: 10209
Ahmadi Fahandar M, Hüllermeier E. Learning to Rank based on Analogical Reasoning. In: Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence. ; 2017.
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2017 | Conference Abstract | LibreCat-ID: 5722
Gupta P, Hetzer A, Tornede T, et al. jPL: A Java-based Software Framework for Preference Learning. In: ; 2017.
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2017 | Conference Paper | LibreCat-ID: 10111
Mohr F, Lettmann T, Hüllermeier E. Planning with Independent Task Networks. In: Proceedings of the 40th Annual German Conference on AI (KI 2017). Vol 10505. Lecture Notes in Computer Science. Springer; 2017:193-206.
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2017 | Conference Paper | LibreCat-ID: 10205
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.
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2017 | Conference Paper | LibreCat-ID: 10212
Hoffmann F, Hüllermeier E, Mikut R. (Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017. In: ; 2017.
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2017 | Journal Article | LibreCat-ID: 10267
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.
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2017 | Encyclopedia Article | LibreCat-ID: 10589
Fürnkranz J, Hüllermeier E. Preference Learning. In: Encyclopedia of Machine Learning and Data Mining. ; 2017:1000-1005.
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2017 | Conference Paper | LibreCat-ID: 10213
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.
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2017 | Conference Paper | LibreCat-ID: 10206
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.
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2017 | Journal Article | LibreCat-ID: 10268
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.
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2017 | Mastersthesis | LibreCat-ID: 5724
Hetzer A, Tornede T. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. Paderborn; 2017.
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2017 | Conference Paper | LibreCat-ID: 71
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
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2017 | Conference Paper | LibreCat-ID: 115
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.
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2017 | Conference Paper | LibreCat-ID: 10214
Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierarchical Planning Versus Evolutionary Optimization . In: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017. ; 2017:149-166.
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2017 | Conference Paper | LibreCat-ID: 10207
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.
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2017 | Journal Article | LibreCat-ID: 10269
Hüllermeier E. From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection. The Computing Research Repository  (CoRR). 2017.
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2017 | Conference Paper | LibreCat-ID: 3325
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
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