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428 Publications


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 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. Universität Paderborn, 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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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 | 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: 10145
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–58.
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2018 | Book Chapter | LibreCat-ID: 10152
Mencia, E. Loz., et al. “Learning Interpretable Rules for Multi-Label Classification.” Explainable and Interpretable Models in Computer Vision and Machine Learning, edited by H. Jair Escalante et al., Springer, 2018, pp. 81–113.
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2018 | Conference Abstract | LibreCat-ID: 1379
Seemann, Nina, et al. “Supporting the Cognitive Process in Annotation Tasks.” Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg, 2018.
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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 | Bachelorsthesis | LibreCat-ID: 5693
Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018.
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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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2017 | Conference Paper | LibreCat-ID: 10204
Ewerth, Ralph, et al. “Estimating Relative Depth in Single Images via Rankboost.” Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 2017, pp. 919–24.
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2017 | Conference Paper | LibreCat-ID: 10209
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017.
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2017 | Conference Paper | LibreCat-ID: 10216
Shaker, Ammar, et al. “Learning TSK Fuzzy Rules from Data Streams.” 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: 1180
Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization.” 27th Workshop Computational Intelligence, 2017.
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2017 | Conference Paper | LibreCat-ID: 15110
Couso, Ines, et al. “Maximum Likelihood Estimation and Coarse Data.” In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, Springer, 2017, pp. 3–16.
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2017 | Bachelorsthesis | LibreCat-ID: 5694
Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn, 2017.
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2017 | Encyclopedia Article | LibreCat-ID: 10589
Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–05.
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2017 | Conference Paper | LibreCat-ID: 10205
Ahmadi Fahandar, Mohsen, et al. “Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening.” Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 2017, pp. 1078–87.
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2017 | Conference Paper | LibreCat-ID: 10212
Hoffmann, F., et al. (Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017. 2017.
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2017 | Journal Article | LibreCat-ID: 10267
Bräuning, M., et al. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application  in Accounting.” European Journal of Operational Research, vol. 258, no. 1, 2017, pp. 295–306.
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2017 | Conference Paper | LibreCat-ID: 15399
Czech, M., et al. “Predicting Rankings of Software Verification Tools.” 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 Abstract | LibreCat-ID: 5722
Gupta, Pritha, et al. JPL: A Java-Based Software Framework for Preference Learning. 2017.
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2017 | Conference Paper | LibreCat-ID: 10213
Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.
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2017 | Journal Article | LibreCat-ID: 10268
Platenius, M. C., et al. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering, vol. 43, no. 8, 2017, pp. 739–59.
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2017 | Conference Paper | LibreCat-ID: 10206
Mohr, Felix, et al. “Planning with Independent Task Networks.” Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 2017, pp. 193–206, doi:10.1007/978-3-319-67190-1_15.
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2017 | Conference Paper | LibreCat-ID: 10207
Czech, M., et al. “Predicting Rankings of Software Verification Tools.” Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 2017, pp. 23–26.
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2017 | Journal Article | LibreCat-ID: 10269
Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy Rule-Based Systems: A Critical Reflection.” The Computing Research Repository  (CoRR), abs/1712.00646, 2017.
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2017 | Conference Paper | LibreCat-ID: 115
Jakobs, Marie-Christine, et al. “Certification Matters for Service Markets.” The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus Uhl, 2017, pp. 7–12.
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2017 | Book Chapter | LibreCat-ID: 18167
Seemann, Nina, et al. “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German.” Proceedings of Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, 2017.
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2017 | Mastersthesis | LibreCat-ID: 5724
Hetzer, Alexander, and Tanja Tornede. 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, Mike, et al. “Predicting Rankings of Software Verification Tools.” Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26, doi:10.1145/3121257.3121262.
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2017 | Book Chapter | LibreCat-ID: 10784
Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, vol. 107, Springer, 2017, pp. 1000–05.
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2017 | Conference Paper | LibreCat-ID: 10208
Couso, Ines, et al. “Maximum Likelihood Estimation and Coarse Data.” Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 2017, pp. 3–16.
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2017 | Conference Paper | LibreCat-ID: 1158
Seemann, Nina, et al. “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German.” Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Association for Computational Linguistics (ACL), 2017, pp. 40–45, doi:10.18653/v1/W17-2206.
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2017 | Conference Paper | LibreCat-ID: 15397
Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies. A Comparison of Two Heuristics.” In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann et al., KIT Scientific Publishing, 2017, pp. 1–12.
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2017 | Report | LibreCat-ID: 72
Czech, Mike, et al. Predicting Rankings of Software Verification Competitions. 2017.
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2017 | Conference Paper | LibreCat-ID: 3325
Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017, doi:10.5445/KSP/1000074341.
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2016 | Encyclopedia Article | LibreCat-ID: 10785
Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer, 2016.
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2016 | Conference Paper | LibreCat-ID: 10223
Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms,  in Proceedings ECML/PKDD-2016.” European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, Riva Del Garda, Italy, 2016, pp. 756–71.
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2016 | Conference Paper | LibreCat-ID: 10228
Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete et al., 2016.
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