Eyke Hüllermeier
First name(s): Eyke
Last name(s): Hüllermeier

Publications of Eyke Hüllermeier sorted by recency
Vu-Linh Nguyen and Eyke Hüllermeier, Reliable Multilabel Classification: Prediction with Partial Abstention (2020), in: Proceedings of the AAAI Conference on Artificial Intelligence, 34:04(5264-5271)
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Eyke Hüllermeier, Johannes Fürnkranz and Eneldo Loza Mencía, Conformal Rule-Based Multi-label Classification, in: KI 2020: Advances in Artificial Intelligence, Springer, Cham, 2020
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Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen and Eyke Hüllermeier, Learning Gradient Boosted Multi-label Classification Rules, in: Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pages 124--140, Springer, 2020
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Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía and Johannes Fürnkranz, On Aggregation in Ensembles of Multilabel Classifiers, in: Discovery Science, pages 533--547, Springer International Publishing, 2020
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Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier and Michael Rapp, Learning Interpretable Rules for Multi-label Classification, in: Explainable and Interpretable Models in Computer Vision and Machine Learning, pages 81--113, Springer-Verlag, 2018
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Johannes Fürnkranz and Eyke Hüllermeier, Special Issue on Discovery Science (2016), in: Information Sciences, 329(849--850)
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Jinseok Nam, Jungi Kim, Eneldo Loza Mencía, Iryna Gurevych and Johannes Fürnkranz, Large-Scale Multi-label Text Classification - Revisiting Neural Networks, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-14), Part 2, pages 437--452, Springer Berlin Heidelberg, 2014
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Julius Stecher, Frederik Janssen and Johannes Fürnkranz, Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-14), Part 3, pages 114--129, Springer, 2014
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Special Issue on Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3
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Eyke Hüllermeier and Johannes Fürnkranz, Editorial: Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3(185--189)
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning, in: Encyclopedia of the Sciences of Learning, pages 986, Springer-Verlag, 2012
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Eyke Hüllermeier and Johannes Fürnkranz, Learning from Label Preferences, in: Proceedings of the 22nd International Conference on Algorithmic Learning Theory (ALT-11), pages 38, Springer, 2011
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Eyke Hüllermeier and Johannes Fürnkranz, Learning from Label Preferences, in: Proceedings of the 14th International Conference on Discovery Science (DS-11), pages 2--17, Springer, 2011
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Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier and Sang-Hyeun Park, Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning, in: Proceedings of the 22nd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011, Athens, Greece), Part I, pages 312--327, Springer, 2011
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning and Ranking by Pairwise Comparison, in: Preference Learning, pages 65--82, Springer-Verlag, 2010
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning: An Introduction, in: Preference Learning, pages 1--17, Springer-Verlag, 2010
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Preference Learning, Springer-Verlag, 2010
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Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop, Austrian Research Institute for Artificial Intelligence, 2003
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Johannes Fürnkranz and Eyke Hüllermeier, Pairwise Preference Learning and Ranking, in: Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop, 2003
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Johannes Fürnkranz and Eyke Hüllermeier, Pairwise Preference Learning and Ranking, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2003-14, 2003
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Grigorios Tsoumakas, Eneldo Loza Mencía, Ioannis Katakis, Sang-Hyeun Park and Johannes Fürnkranz, On the Combination of Two Decompositive Multi-Label Classification Methods, in: Proceedings of the ECML PKDD 2009 Workshop on Preference Learning (PL-09, Bled, Slovenia), pages 114--129, 2009
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Johannes Fürnkranz, Eyke Hüllermeier and Stijn Vanderlooy, Binary Decomposition Methods for Multipartite Ranking, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-09), pages 359--374, Springer-Verlag, 2009
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning, in: Encyclopedia of Machine Learning, pages 789--795, Springer-Verlag, 2010
Sang-Hyeun Park and Johannes Fürnkranz, Multi-Label Classification with Label Constraints, in: Proceedings of the ECML PKDD 2008 Workshop on Preference Learning (PL-08, Antwerp, Belgium), pages 157--171, 2008
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Eyke Hüllermeier and Johannes Fürnkranz, Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants, in: Preferences and Similarities, pages 283--304, Springer-Verlag, 2008
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Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng and Klaus Brinker, Label Ranking by Learning Pairwise Preferences (2008), in: Artificial Intelligence, 172:16–17(1897--1916)
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Eyke Hüllermeier and Johannes Fürnkranz, On Predictive Accuracy and Risk Minimization in Pairwise Label Ranking (2010), in: Journal of Computer and System Sciences, 76:1(49--62)
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Eyke Hüllermeier and Johannes Fürnkranz, On Minimizing the Position Error in Label Ranking, in: Proceedings of 18th European Conference on Machine Learning (ECML-07), pages 583--590, Springer-Verlag, 2007
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Jan-Nikolas Sulzmann, Johannes Fürnkranz and Eyke Hüllermeier, On Pairwise Naive Bayes Classifiers, in: Proceedings of 18th European Conference on Machine Learning (ECML-07), pages 371--381, Springer-Verlag, 2007
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Eyke Hüllermeier and Johannes Fürnkranz, On Minimizing the Position Error in Label Ranking, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-04, 2007
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Klaus Brinker, Johannes Fürnkranz and Eyke Hüllermeier, Label Ranking by Learning Pairwise Preferences, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-01, 2007
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Klaus Brinker, Johannes Fürnkranz and Eyke Hüllermeier, A Unified Model for Multilabel Classification and Ranking, in: Proceedings of the 17th European Conference on Artificial Intelligence (ECAI-06), pages 489--493, 2006
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Eyke Hüllermeier, Johannes Fürnkranz and Jürgen Beringer, On Position Error and Label Ranking through Iterated Choice, in: {LWA 2005, Lernen Wissensentdeckung Adaptivität}, pages 158--163, German Research Center for Artificial Intelligence (DFKI), 2005
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Eyke Hüllermeier and Johannes Fürnkranz, Learning Label Preferences: Ranking Error versus Position Error, in: Advances in Intelligent Data Analysis: Proceedings of the 6th International Symposium (IDA-05), pages 180--191, Springer-Verlag, 2005
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning (2005), in: Künstliche Intelligenz, 19:1(60--61)
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Eyke Hüllermeier and Johannes Fürnkranz, Ranking by Pairwise Comparison: A Note on Risk Minimization, in: Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE-04), 2004
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Eyke Hüllermeier and Johannes Fürnkranz, Comparison of Ranking Procedures in Pairwise Preference Learning, in: Proceedings of the 10th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-04), 2004
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Klaus Brinker and Eyke Hüllermeier, Case-Based Label Ranking, in: Proceedings of the 17th European Conference on Machine Learning (ECML-06), pages 566--573, Springer-Verlag, 2006
Johannes Fürnkranz and Eyke Hüllermeier, Pairwise Preference Learning and Ranking, in: Proceedings of the 14th European Conference on Machine Learning (ECML-03), pages 145--156, Springer-Verlag, 2003
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