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449 Publications
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). Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn; 2018:3469-3477.
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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 | Book Chapter | LibreCat-ID: 10152
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.
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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: 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 | 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 | 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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2017 | Journal Article | LibreCat-ID: 24152
Ramaswamy A, Bhatnagar S. Analysis of gradient descent methods with nondiminishing bounded errors. IEEE Transactions on Automatic Control. 2017;63(5):1465-1471.
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2017 | Journal Article | LibreCat-ID: 24153
Ramaswamy A, Bhatnagar S. A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions. Mathematics of Operations Research. 2017;42(3):648-661.
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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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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: 1158
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
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| DOI
2017 | Bachelorsthesis | LibreCat-ID: 5694
Schnitker NN. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn; 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 | Mastersthesis | LibreCat-ID: 5724
Hetzer A, Tornede T. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. Universität 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 | Report | LibreCat-ID: 72
Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software Verification Competitions.; 2017.
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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 | Book Chapter | LibreCat-ID: 10784
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.
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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: 15397
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.
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2017 | Conference Paper | LibreCat-ID: 15399
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.
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2017 | Conference Paper | LibreCat-ID: 15110
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.
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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: 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: 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. doi:10.1007/978-3-319-67190-1_15
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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 | Conference Paper | LibreCat-ID: 10208
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.
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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 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 | 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: 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 | 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 | 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 | 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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2016 | Journal Article | LibreCat-ID: 24154
Ramaswamy A, Bhatnagar S. Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem. Stochastics. 2016;88(8):1173-1187.
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2016 | Journal Article | LibreCat-ID: 3318
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
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2016 | Journal Article | LibreCat-ID: 190
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
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2016 | Conference Paper | LibreCat-ID: 184
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
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2016 | Encyclopedia Article | LibreCat-ID: 10785
Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. Encyclopedia of Machine Learning and Data Mining. Springer; 2016.
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2016 | Conference Paper | LibreCat-ID: 15400
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.
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2016 | Conference Paper | LibreCat-ID: 15401
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.
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2016 | Conference Paper | LibreCat-ID: 15402
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.
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2016 | Conference Paper | LibreCat-ID: 15403
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.
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2016 | Conference Paper | LibreCat-ID: 15404
Schäfer D, Hüllermeier E. Plackett-Luce networks for dyad ranking. In: In Workshop LWDA “Lernen, Wissen, Daten, Analysen” Potsdam, Germany. ; 2016.
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2016 | Conference Paper | LibreCat-ID: 15111
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.
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2016 | Journal Article | LibreCat-ID: 16041
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.
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2016 | Dissertation | LibreCat-ID: 141
Mohr F. Towards Automated Service Composition Under Quality Constraints. Universität Paderborn; 2016. doi:10.17619/UNIPB/1-171
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| DOI
2016 | Book Chapter | LibreCat-ID: 10214
Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. Encyclopedia of Machine Learning and Data Mining. Springer; 2016.
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2016 | Conference (Editor) | LibreCat-ID: 10221
Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings 26. Workshop Computational Intelligence KIT Scientific Publishing, Karlsruhe, Germany.; 2016.
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