Publikationen

Editorship

• Mikut, Ralf; Hüllermeier, Eyke; Hoffmann, Frank (eds.) (2017)
  Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017
  Karlsruhe: KIT Scientific Publishing (full text available)
  
• Hoffmann, Frank; Hüllermeier, Eyke; Mikut, Ralf (eds.) (2016)
  Proceedings. 26. Workshop Computational Intelligence, Dortmund, 24. - 25. November 2016
  Karlsruhe: KIT Scientific Publishing (full text available)
  
• Hüllermeier, Eyke; Minor, Mirjam (eds.) (2015)
  Case-Based Reasoning Research and Development. 23rd International Conference, ICCBR 2015, Frankfurt am Main, Germany, September 28-30, 2015. Proceedings
  Lecture Notes in Computer Science, Vol. 9343. Cham: Springer
  
• Hoffmann, Frank; Hüllermeier, Eyke (eds.) (2015)
  Proceedings. 25. Workshop Computational Intelligence, Dortmund, 26. - 27. November 2015
  Schriftenreihe des Instituts für Angewandte Informatik - Automatisierungstechnik, Karlsruher Institut für Technologie, Vol. 54. Karlsruhe: KIT Scientific Publishing (full text available)
  
• Calders, Toon; Esposito, Floriana; Hüllermeier, Eyke; Meo, Rosa (eds.) (2014)
  Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part I
  Lecture Notes in Computer Science, Vol. 8724. Berlin, Heidelberg: Springer
  
• Fürnkranz, Johannes; Hüllermeier, Eyke; Rudin, Cynthia; Sanner, Scott; Słowiński, Roman (2014)
  Preference Learning. Report from Dagstuhl Seminar 14101
  Dagstuhl Reports, Vol. 4. Dagstuhl: Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik (full text available)
  
• Hoffmann, Frank; Hüllermeier, Eyke (eds.) (2013)
  Proceedings. 23. Workshop Computational Intelligence, Dortmund, 5. - 6. Dezember 2013
  Schriftenreihe des Instituts für Angewandte Informatik - Automatisierungstechnik, Karlsruher Institut für Technologie, Vol. 46. Karlsruhe: KIT Scientific Publishing (full text available)
  
• Fürnkranz, Johannes; Hüllermeier, Eyke (eds.) (2010)
  Preference Learning
  Berlin: Springer
  
• Hoffmann, Frank; Hüllermeier, Eyke (eds.) (2009)
  Proceedings. 19. Workshop Computational Intelligence, Dortmund, 2. - 4. Dezember 2009
  Schriftenreihe des Instituts für Angewandte Informatik - Automatisierungstechnik, Universität Karlsruhe (TH), Vol. 29. Karlsruhe: KIT Scientific Publishing (full text available)
  

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Journal article

• Verwimp, Eli; Aljundi, Rahaf; Ben-David, Shai; Bethge, Matthias; Cossu, Andrea; Gepperth, Alexander; Hayes, Tyler L.; Hüllermeier, Eyke; Kanan, Christopher; Kudithipudi, Dhireesha; Lampert, Christoph H.; Mundt, Martin; Pascanu, Razvan; Popescu, Adrian; Tolias, Andreas S.; van de Weijer, Joost; Liu, Bing; Lomonaco, Vincenzo; Tuytelaars, Tinne; van de Ven, Gido M. (2024)
  Continual Learning: Applications and the Road Forward
  In: Transactions on Machine Learning Research (full text available)
  
• Hüllermeier, Eyke; Słowiński, Roman (2024)
  Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies–part I
  In: 4OR, Vol. 22, No. 2: pp. 179-209
  
• Heid, Stefan; Hanselle, Jonas; Fürnkranz, Johannes; Hüllermeier, Eyke (2024)
  Learning decision catalogues for situated decision making: The case of scoring systems
  In: International Journal of Approximate Reasoning, Vol. 171 (full text available)
  
• Fumagalli, Fabian; Muschalik, Maximilian; Hüllermeier, Eyke; Hammer, Barbara (2023)
  Incremental permutation feature importance (iPFI): towards online explanations on data streams
  In: Machine Learning, Vol. 112, No. 12: pp. 4863-4903
  
• Javanmardi, Alireza; Hüllermeier, Eyke (2023)
  Conformal Prediction Intervals for Remaining Useful Lifetime Estimation
  In: International Journal of Prognostics and Health Management, Vol. 14, No. 2
  
• Tornede, Alexander; Gehring, Lukas; Tornede, Tanja; Wever, Marcel; Hüllermeier, Eyke (2023)
  Algorithm selection on a meta level
  In: Machine Learning, Vol. 112, No. 4: pp. 1253-1286
  
• Dellnitz, Michael; Hüllermeier, Eyke; Lücke, Marvin; Ober-Blöbaum, Sina; Offen, Christian; Peitz, Sebastian; Pfannschmidt, Karlson (2023)
  Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning
  In: SIAM Journal on Scientific Computing, Vol. 45, No. 2: pp. A579-A595
  
• Tornede, Tanja; Tornede, Alexander; Hanselle, Jonas; Mohr, Felix; Wever, Marcel; Hüllermeier, Eyke (2023)
  Towards Green Automated Machine Learning: Status Quo and Future Directions
  In: Journal of Artificial Intelligence Research, Vol. 77: pp. 427-457
  
• Rapp, Michael; Fürnkranz, Johannes; Hüllermeier, Eyke (2023)
  On the efficient implementation of classification rule learning
  In: Advances in Data Analysis and Classification [forthcoming]
  
• Bengs, Viktor; Hüllermeier, Eyke (2022)
  Multi-armed bandits with censored consumption of resources
  In: Machine Learning, Vol. 112, No. 2: pp. 217-240
  
• Schede, Elias; Brandt, Jasmin; Tornede, Alexander; Wever, Marcel; Bengs, Viktor; Hüllermeier, Eyke; Tierney, Kevin (2022)
  A Survey of Methods for Automated Algorithm Configuration
  In: Journal of Artificial Intelligence Research, Vol. 75: pp. 425-487
  
• Muschalik, Maximilian; Fumagalli, Fabian; Hammer, Barbara; Hüllermeier, Eyke (2022)
  Agnostic Explanation of Model Change based on Feature Importance
  In: KI - Künstliche Intelligenz, Vol. 36, No. 3-4: pp. 211-224
  
• Hüllermeier, Eyke; Wever, Marcel; Loza Mencia, Eneldo; Fürnkranz, Johannes; Rapp, Michael (2022)
  A flexible class of dependence-aware multi-label loss functions
  In: Machine Learning, Vol. 111, No. 2: pp. 713-737 (full text available)
  
• Pfannschmidt, Karlson; Gupta, Pritha; Haddenhorst, Björn; Hüllermeier, Eyke (2022)
  Learning context-dependent choice functions
  In: International Journal of Approximate Reasoning, Vol. 140: pp. 116-155
  
• Nguyen, Vu-Linh; Shaker, Mohammad Hossein; Hüllermeier, Eyke (2022)
  How to measure uncertainty in uncertainty sampling for active learning
  In: Machine Learning, Vol. 111, No. 1: pp. 89-122
  
• Abbaszadeh, Sadegh; Hüllermeier, Eyke (2021)
  Machine Learning With the Sugeno Integral: The Case of Binary Classification
  In: IEEE Transactions on Fuzzy Systems, No. 12: pp. 3723-3733
  
• Nguyen, Vu-Linh; Hüllermeier, Eyke (2021)
  Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence
  In: Journal of Artificial Intelligence Research, Vol. 72: pp. 613-665
  
• Ramaswamy, Arunselvan; Hüllermeier, Eyke (2021)
  Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis
  In: IEEE Transactions on Artificial Intelligence: pp. 1-1
  
• Rohlfing, Katharina J.; Cimiano, Philipp; Scharlau, Ingrid; Matzner, Tobias; Buhl, Heike M.; Buschmeier, Hendrik; Esposito, Elena; Grimminger, Angela; Hammer, Barbara; Hab-Umbach, Reinhold; Horwath, Ilona; Hüllermeier, Eyke; Kern, Friederike; Kopp, Stefan; Thommes, Kirsten; Ngonga Ngomo, Axel-Cyrille; Schulte, Carsten; Wachsmuth, Henning; Wagner, Petra; Wrede, Britta (2021)
  Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems
  In: IEEE Transactions on Cognitive and Developmental Systems, Vol. 13, No. 3: pp. 717-728 (full text available)
  
• Wever, Marcel; Tornede, Alexander; Mohr, Felix; Hüllermeier, Eyke (2021)
  AutoML for Multi-Label Classification: Overview and Empirical Evaluation
  In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, No. 9: pp. 3037-3054 (full text available)
  
• Haddenhorst, Björn; Bengs, Viktor; Hüllermeier, Eyke (2021)
  On testing transitivity in online preference learning
  In: Machine Learning, Vol. 110, No. 8: pp. 2063-2084
  
• Lienen, Julian; Hüllermeier, Eyke (2021)
  Instance weighting through data imprecisiation
  In: International Journal of Approximate Reasoning, Vol. 134: pp. 1-14
  
• Campagner, Andrea; Ciucci, Davide; Hüllermeier, Eyke (2021)
  Rough set-based feature selection for weakly labeled data
  In: International Journal of Approximate Reasoning: pp. 150-167
  
• Shaker, Ammar; Hüllermeier, Eyke (2021)
  TSK-Streams: learning TSK fuzzy systems for regression on data streams
  In: Data Mining and Knowledge Discovery, No. 5: pp. 1941-1971
  
• Mortier, Thomas; Wydmuch, Marek; Dembczyński, Krzysztof; Hüllermeier, Eyke; Waegeman, Willem (2021)
  Efficient set-valued prediction in multi-class classification
  In: Data Mining and Knowledge Discovery, Vol. 35, No. 4: pp. 1435-1469
  
• Hüllermeier, Eyke; Waegeman, Willem (2021)
  Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods
  In: Machine Learning, No. 3: pp. 457-506
  
• Weber, Daniel; Heid, Stefan; Bode, Henrik; Lange, Jarren H.; Hüllermeier, Eyke; Wallscheid, Oliver (2021)
  Safe Bayesian Optimization for Data-Driven Power Electronics Control Design in Microgrids: From Simulations to Real-World Experiments
  In: IEEE Access, Vol. 9: pp. 35654-35669
  
• Mohr, Felix; Wever, Marcel; Tornede, Alexander; Hüllermeier, Eyke (2021)
  Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning
  In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, No. 9: pp. 3055-3066
  
• Bengs, Viktor; Busa-Fekete, Róbert; Mesaoudi-Paul, Adil El; Hüllermeier, Eyke (2021)
  Preference-based Online Learning with Dueling Bandits: A Survey
  In: Journal of Machine Learning Research, Vol. 22, No. 7: pp. 1-108
  
• Campagner, Andrea; Ciucci, Davide; Hüllermeier, Eyke (2021)
  Rough set-based feature selection for weakly labeled data
  In: International Journal of Approximate Reasoning, Vol. 136: pp. 150-167
  
• Haddenhorst, Björn; Bengs, Viktor; Hüllermeier, Eyke (2021)
  On testing transitivity in online preference learning
  In: Machine Learning, Vol. 110, No. 8: pp. 2063-2084
  
• Lienen, Julian; Hüllermeier, Eyke (2021)
  Instance weighting through data imprecisiation
  In: International Journal of Approximate Reasoning, Vol. 134: pp. 1-14
  
• Mortier, Thomas; Wydmuch, Marek; Dembczynski, Krzysztof; Hüllermeier, Eyke; Waegeman, Willem (2021)
  Efficient set-valued prediction in multi-class classification
  In: Data Mining and Knowledge Discovery, Vol. 35, No. 4: pp. 1435-1469
  
• Nguyen, Vu-Linh; Hüllermeier, Eyke (2021)
  Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence
  In: Journal of Artificial Intelligence Research, Vol. 72: pp. 613-665
  
• Pfannschmidt, Karlson; Gupta, Pritha; Haddenhorst, Björn; Hüllermeier, Eyke (2021)
  Learning context-dependent choice functions
  In: International Journal of Approximate Reasoning, Vol. 140: pp. 116-155
  
• Shaker, Ammar; Hüllermeier, Eyke (2021)
  TSK-Streams: learning TSK fuzzy systems for regression on data streams
  In: Data Mining and Knowledge Discovery, Vol. 35, No. 5: pp. 1941-1971
  
• Heid, Stefan; Weber, Daniel; Bode, Henrik; Hüllermeier, Eyke; Wallscheid, Oliver (2020)
  OMG: A Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control
  In: Journal of Open Source Software (JOSS), Vol. 5, No. 54
  
• Rohlfing, Katharina J.; Leonardi, Giuseppe; Nomikou, Iris; Raczaszek-Leonardi, Joanna; Hüllermeier, Eyke (2020)
  Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches
  In: IEEE Transactions on Cognitive and Developmental Systems, Vol. 12, No. 2: pp. 260-271
  
• Richter, Cedric; Hüllermeier, Eyke; Jakobs, Marie-Christine; Wehrheim, Heike (2020)
  Algorithm selection for software validation based on graph kernels
  In: Automated Software Engineering, Vol. 27, No. 1-2: pp. 153-186
  
• Haddenhorst, Björn; Hüllermeier, Eyke; Kolb, Martin (2020)
  Generalized transitivity: A systematic comparison of concepts with an application to preferences in the Babington Smith model
  In: International Journal of Approximate Reasoning, Vol. 119: pp. 373-407
  
• Waegeman, Willem; Dembczyński, Krzysztof; Hüllermeier, Eyke (2019)
  Multi-target prediction: a unifying view on problems and methods
  In: Data Mining and Knowledge Discovery, Vol. 33, No. 2: pp. 293-324
  
• Couso, Ines; Borgelt, Christian; Hüllermeier, Eyke; Kruse, Rudolf (2019)
  Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning
  In: IEEE Computational Intelligence Magazine, Vol. 14, No. 1: pp. 31-44
  
• Tagne, Vidal Kamdem; Fotso, Siméon; Fono, Louis Aimé; Hüllermeier, Eyke (2019)
  Choice Functions Generated by Mallows and Plackett–Luce Relations
  In: New Mathematics and Natural Computation, Vol. 15, No. 2: pp. 191-213
  
• Henzgen, Sascha; Hüllermeier, Eyke (2019)
  Mining Rank Data
  In: ACM Transactions on Knowledge Discovery from Data, Vol. 13, No. 6: pp. 1-36
  
• Abiteboul, Serge; Arenas, Marcelo; Barceló, Pablo; Bienvenu, Meghyn; Calvanese, Diego; David, Claire; Hull, Richard; Hüllermeier, Eyke; Kimelfeld, Benny; Libkin, Leonid; Martens, Wim; Milo, Tova; Murlak, Filip; Neven, Frank; Ortiz, Magdalena; Schwentick, Thomas; Stoyanovich, Julia; Su, Jianwen; Suciu, Dan; Vianu, Victor; Yi, Ke (2018)
  Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)
  In: Dagstuhl Manifestos, Vol. 7, No. 1: pp. 1-29
  
• Schäfer, Dirk; Hüllermeier, Eyke (2018)
  Dyad ranking using Plackett–Luce models based on joint feature representations
  In: Machine Learning, Vol. 107, No. 5: pp. 903-941
  
• Melnikov, Vitalik; Hüllermeier, Eyke (2018)
  On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis
  In: Machine Learning, Vol. 107, No. 8-10: pp. 1537-1560
  
• Mohr, Felix; Wever, Marcel; Hüllermeier, Eyke (2018)
  ML-Plan: Automated machine learning via hierarchical planning
  In: Machine Learning, Vol. 107, No. 8-10: pp. 1495-1515
  
• Hesse, Michael; Timmermann, Julia; Hüllermeier, Eyke; Trächtler, Ansgar (2018)
  A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart
  In: Procedia Manufacturing, Vol. 24: pp. 15-20
  
• Bräuning, Michael; Hüllermeier, Eyke; Keller, Tobias; Glaum, Martin (2017)
  Lexicographic preferences for predictive modeling of human decision making: A new machine learning method with an application in accounting
  In: European Journal of Operational Research, Vol. 258, No. 1: pp. 295-306
  
• Platenius, Marie C.; Shaker, Ammar; Becker, Matthias; Hüllermeier, Eyke; Schafer, Wilhelm (2017)
  Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic
  In: IEEE Transactions on Software Engineering, Vol. 43, No. 8: pp. 739-759
  
• Abiteboul, Serge; Arenas, Marcelo; Barceló, Pablo; Bienvenu, Meghyn; Calvanese, Diego; David, Claire; Hull, Richard; Hüllermeier, Eyke; Kimelfeld, Benny; Libkin, Leonid; Martens, Wim; Milo, Tova; Murlak, Filip; Neven, Frank; Ortiz, Magdalena; Schwentick, Thomas; Stoyanovich, Julia; Su, Jianwen; Suciu, Dan; Vianu, Victor; Yi, Ke (2016)
  Research Directions for Principles of Data Management (Abridged)
  In: SIGMOD Record, Vol. 45, No. 4: pp. 5–17
  
• Bräuning, Michael; Hüllermeier, Eyke (2016)
  Learning Conditional Lexicographic Preference Tree
  In: Archives of data science. Series A, Vol. 1, No. 1: pp. 41-55
  
• Leinweber, Matthias; Fober, Thomas; Strickert, Marc; Baumgartner, Lars; Klebe, Gerhard; Freisleben, Bernd; Hüllermeier, Eyke (2016)
  CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites
  In: IEEE Transactions on Knowledge and Data Engineering, Vol. 28, No. 6: pp. 1423-1434
  
• Riemenschneider, Mona; Senge, Robin; Neumann, Ursula; Hüllermeier, Eyke; Heider, Dominik (2016)
  Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification
  In: BioData Mining, Vol. 9
  
• Melnikov, Vitalik; Hüllermeier, Eyke; Kaimann, Daniel; Frick, Bernd; Gupta, Pritha (2016)
  Pairwise versus Pointwise Ranking: A Case Study
  In: Schedae Informaticae, Vol. 25: pp. 73-83
  
• Hüllermeier, Eyke (2015)
  From knowledge-based to data-driven fuzzy modeling
  In: Informatik-Spektrum, Vol. 38, No. 6: pp. 500-509
  
• Hüllermeier, Eyke (2015)
  Does machine learning need fuzzy logic?
  In: Fuzzy Sets and Systems, Vol. 281: pp. 292-299
  
• Shaker, Ammar; Hüllermeier, Eyke (2015)
  Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study
  In: Neurocomputing, Vol. 150, No. A: pp. 250-264
  
• Garcia-Jimenez, Santiago; Bustince, Humberto; Hüllermeier, Eyke; Mesiar, Radko; Pal, Nikhil R.; Pradera, Ana (2015)
  Overlap Indices: Construction of and Application to Interpolative Fuzzy Systems
  In: IEEE Transactions on Fuzzy Systems, Vol. 23, No. 4: pp. 1259-1273
  
• Senge, Robin; Hüllermeier, Eyke (2015)
  Fast Fuzzy Pattern Tree Learning for Classification
  In: IEEE Transactions on Fuzzy Systems, Vol. 23, No. 6: pp. 2024-2033
  
• Waegeman, Willem; Dembczyński, Krzysztof; Jachnik, Arkadiusz; Cheng, Weiwei; Hüllermeier, Eyke (2014)
  On the Bayes-Optimality of F-Measure Maximizers
  In: Journal of Machine Learning Research, Vol. 15: pp. 3513-3568
  
• Agarwal, Manish; Fallah Tehrani, Ali; Hüllermeier, Eyke (2014)
  Preference-based Learning of Ideal Solutions in TOPSIS-like Decision Models
  In: Journal of Multi-Criteria Decision Analysis, Vol. 22, No. 3-4: pp. 175-183
  
• Calders, Toon; Esposito, Floriana; Hüllermeier, Eyke; Meo, Rosa (2014)
  Guest editors’ introduction: special issue of the ECML/PKDD 2014 journal track
  In: Data Mining and Knowledge Discovery, Vol. 28, No. 5-6: pp. 1129-1133
  
• Busa-Fekete, Róbert; Szörényi, Balázs; Weng, Paul; Cheng, Weiwei; Hüllermeier, Eyke (2014)
  Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm
  In: Machine Learning, Vol. 97, No. 3: pp. 327-351
  
• Calders, Toon; Esposito, Floriana; Hüllermeier, Eyke; Meo, Rosa (2014)
  Guest Editors’ introduction: special issue of the ECML/PKDD 2014 journal track
  In: Machine Learning, Vol. 97, No. 1-2: pp. 1-3
  
• Henzgen, Sascha; Strickert, Marc; Hüllermeier, Eyke (2014)
  Visualization of evolving fuzzy rule-based systems
  In: Evolving Systems, Vol. 5, No. 3: pp. 175-191
  
• Hüllermeier, Eyke (2014)
  Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization
  In: International Journal of Approximate Reasoning, Vol. 55, No. 7: pp. 1519-1534
  
• Hüllermeier, Eyke (2014)
  Rejoinder on “Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization”
  In: International Journal of Approximate Reasoning, Vol. 55, No. 7: pp. 1609-1613
  
• Senge, Robin; Bösner, Stefan; Dembczyński, Krzysztof; Haasenritter, Jörg; Hirsch, Oliver; Donner-Banzhoff, Norbert; Hüllermeier, Eyke (2014)
  Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty
  In: Information Sciences, Vol. 255: pp. 16-29
  
• Donner-Banzhoff, Norbert; Haasenritter, Jörg; Hüllermeier, Eyke; Viniol, Annika; Bösner, Stefan; Becker, Annette (2014)
  The comprehensive diagnostic study is suggested as a design to model the diagnostic process
  In: Journal of Clinical Epidemiology, Vol. 67, No. 2: pp. 124-132 (full text available)
  
• Strickert, Marc; Bunte, Kerstin; Schleif, Frank-Michael; Hüllermeier, Eyke (2014)
  Correlation-based embedding of pairwise score data
  In: Neurocomputing, Vol. 141: pp. 97-109
  
• Montañes, Elena; Senge, Robin; Barranquero, Jose; Ramón Quevedo, José; José del Coz, Juan; Hüllermeier, Eyke (2014)
  Dependent binary relevance models for multi-label classification
  In: Pattern Recognition, Vol. 47, No. 3: pp. 1494-1508
  
• Krotzky, Timo; Fober, Thomas; Hüllermeier, Eyke; Klebe, Gerhard (2014)
  Extended Graph-Based Models for Enhanced Similarity Search in Cavbase
  In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 11, No. 5: pp. 878-890
  
• Stock, Michiel; Fober, Thomas; Hüllermeier, Eyke; Glinca, Serghei; Klebe, Gerhard; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem (2014)
  Identification of Functionally Related Enzymes by Learning-to-Rank Methods
  In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 11, No. 6: pp. 1157-1169
  
• Mernberger, Marco; Moog, Daniel; Stork, Simone; Zauner, Stefan; Maier, Uwe G.; Hüllermeier, Eyke (2014)
  Protein Sub-Cellular Localization Prediction for Special Compartments via Optimized Time Series Distances
  In: Journal of Bioinformatics and Computational Biology, Vol. 12, No. 1: pp. 1350016
  
• Krempl, Georg; Žliobaite, Indre; Brzeziński, Dariusz; Hüllermeier, Eyke; Last, Mark; Lemaire, Vincent; Noack, Tino; Shaker, Ammar; Sievi, Sonja; Spiliopoulou, Myra; Stefanowski, Jerzy (2014)
  Open challenges for data stream mining research
  In: ACM SIGKDD Explorations Newsletter, Vol. 16, No. 1: pp. 1-10
  
• Shaker, Ammar; Hüllermeier, Eyke (2014)
  Survival analysis on data streams: Analyzing temporal events in dynamically changing environments
  In: International Journal of Applied Mathematics and Computer Science, Vol. 24, No. 1: pp. 199-212 (full text available)
  
• Shaker, Ammar; Senge, Robin; Hüllermeier, Eyke (2013)
  Evolving fuzzy pattern trees for binary classification on data streams
  In: Information Sciences, Vol. 220: pp. 34-45
  
• Haasenritter, Jörg; Viniol, Annika; Becker, Annette; Bösner, Stefan; Hüllermeier, Eyke; Senge, Robin; Donner-Banzhoff, Norbert (2013)
  Diagnose im Kontext – eine erweiterte Perspektive
  In: Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, Vol. 107, No. 9-10: pp. 585-591
  
• Heider, Dominik; Senge, Robin; Cheng, Weiwei; Hüllermeier, Eyke (2013)
  Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistance prediction
  In: Bioinformatics, Vol. 29, No. 16: pp. 1946-1952
  
• Bösner, Stefan; Bönisch, Katharina; Haasenritter, Jörg; Schlegel, Patrice; Hüllermeier, Eyke; Donner-Banzhoff, Norbert (2013)
  Chest pain in primary care: is the localization of pain diagnostically helpful in the critical evaluation of patients? - A cross sectional study
  In: BMC Family Practice, Vol. 14 (full text available)
  
• Fober, Thomas; Mernberger, Marco; Klebe, Gerhard; Hüllermeier, Eyke (2012)
  Fingerprint Kernels for Protein Structure Comparison
  In: Molecular Informatics, Vol. 31, No. 6-7: pp. 443-452
  
• Fürnkranz, Johannes; Hüllermeier, Eyke; Cheng, Weiwei; Park, Sang-Hyeun (2012)
  Preference-based reinforcement learning: a formal framework and a policy iteration algorithm
  In: Machine Learning, Vol. 89, No. 1-2: pp. 123-156
  
• Tehrani, Ali Fallah; Cheng, Weiwei; Dembczyński, Krzysztof; Hüllermeier, Eyke (2012)
  Learning monotone nonlinear models using the Choquet integral
  In: Machine Learning, Vol. 89, No. 1-2: pp. 183-211
  
• Shaker, Ammar; Hüllermeier, Eyke (2012)
  IBLStreams: a system for instance-based classification and regression on data streams
  In: Evolving Systems, Vol. 3, No. 4: pp. 235-249
  
• Ruiz, M. Dolores; Hüllermeier, Eyke (2012)
  A formal and empirical analysis of the fuzzy gamma rank correlation coefficient
  In: Information Sciences, Vol. 206: pp. 1-17
  
• Bustince, Humberto; Pagola, Miguel; Mesiar, Radko; Hüllermeier, Eyke; Herrera, Francisco (2012)
  Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons
  In: IEEE Transactions on Fuzzy Systems, Vol. 20, No. 3: pp. 405-415
  
• Hüllermeier, Eyke; Rifqi, Maria; Henzgen, Sascha; Senge, Robin (2012)
  Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures
  In: IEEE Transactions on Fuzzy Systems, Vol. 20, No. 3: pp. 546-556
  
• Tehrani, Ali Fallah; Cheng, Weiwei; Hüllermeier, Eyke (2012)
  Preference Learning Using the Choquet Integral: The Case of Multipartite Ranking
  In: IEEE Transactions on Fuzzy Systems, Vol. 20, No. 6: pp. 1102-1113
  
• Senge, Robin; Fober, Thomas; Nasiri, Maryam; Hüllermeier, Eyke (2012)
  Fuzzy Pattern Trees: Ein alternativer Ansatz zur Fuzzy-Modellierung
  In: at - Automatisierungstechnik, Vol. 60, No. 10: pp. 622-629
  
• Hoffmann, Frank; Hüllermeier, Eyke; Kroll, Andreas (2012)
  Ausgewählte Beiträge des GMA-Fachausschusses 5.14 “Computational Intelligence”
  In: at - Automatisierungstechnik, Vol. 60, No. 10: pp. 587-588
  
• Dembczyński, Krzysztof; Waegeman, Willem; Cheng, Weiwei; Hüllermeier, Eyke (2012)
  On label dependence and loss minimization in multi-label classification
  In: Machine Learning, Vol. 88, No. 1-2: pp. 5-45
  
• Hüllermeier, Eyke (2011)
  Fuzzy machine learning and data mining
  In: WIREs: Data Mining and Knowledge Discovery, Vol. 1, No. 4: pp. 269-283
  
• Domshlak, Carmel; Hüllermeier, Eyke; Kaci, Souhila; Prade, Henri (2011)
  Preferences in AI: An overview
  In: Artificial Intelligence, Vol. 175, No. 7-8: pp. 1037-1052
  
• Hüllermeier, Eyke (2011)
  Fuzzy sets in machine learning and data mining
  In: Applied Soft Computing, Vol. 11, No. 2: pp. 1493-1505
  
• Mernberger, Marco; Klebe, Gerhard; Hüllermeier, Eyke (2011)
  SEGA: Semiglobal Graph Alignment for Structure-Based Protein Comparison
  In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 8, No. 5: pp. 1330-1343
  
• Fober, Thomas; Glinca, Gerghei; Klebe, Gerhard; Hüllermeier, Eyke (2011)
  Superposition and Alignment of Labeled Point Clouds
  In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 8, No. 6: pp. 1653-1666
  
• Senge, Robin; Hüllermeier, Eyke (2011)
  Top-Down Induction of Fuzzy Pattern Trees
  In: IEEE Transactions on Fuzzy Systems, Vol. 19, No. 2: pp. 241-252
  
• Hirsch, Oliver; Bösner, Stefan; Hüllermeier, Eyke; Senge, Robin; Dembczynski, Krzysztof; Donner-Banzhoff, Norbert (2011)
  Multivariate modeling to identify patterns in clinical data: the example of chest pain
  In: BMC Medical Research Methodology, Vol. 11 (full text available)
  
• Hüllermeier, Eyke; Fürnkranz, Johannes (2010)
  On predictive accuracy and risk minimization in pairwise label ranking
  In: Journal of Computer and System Sciences, Vol. 76, No. 1: pp. 49-62
  
• Hüllermeier, Eyke; Vanderlooy, Stijn (2010)
  Combining predictions in pairwise classification: An optimal adaptive voting strategy and its relation to weighted voting
  In: Pattern Recognition, Vol. 43, No. 1: pp. 128-142
  
• Pfeffer, Patrick; Fober, Thomas; Hüllermeier, Eyke; Klebe, Gerhard (2010)
  GARLig: A Fully Automated Tool for Subset Selection of Large Fragment Spaces via a Self-Adaptive Genetic Algorithm
  In: Journal of Chemical Information and Modeling, Vol. 50, No. 9: pp. 1644-1659
  
• Weskamp, Nils; Hüllermeier, Eyke; Klebe, Gerhard (2009)
  Merging chemical and biological space: Structural mapping of enzyme binding pocket space
  In: Proteins: Structure, Function, and Bioinformatics, Vol. 76, No. 2: pp. 317-330
  
• Hühn, Jens; Hüllermeier, Eyke (2009)
  FURIA: an algorithm for unordered fuzzy rule induction
  In: Data Mining and Knowledge Discovery, Vol. 19, No. 3: pp. 293-319
  
• Cheng, Weiwei; Hüllermeier, Eyke (2009)
  Combining instance-based learning and logistic regression for multilabel classification
  In: Machine Learning, Vol. 76, No. 2-3: pp. 211-225
  
• Hüllermeier, Eyke; Vanderlooy, S. (2009)
  Why Fuzzy Decision Trees are Good Rankers
  In: IEEE Transactions on Fuzzy Systems, Vol. 17, No. 6: pp. 1233-1244
  
• Dubois, Didier; Hüllermeier, Eyke; Prade, Henri (2006)
  Fuzzy methods for case-based recommendation and decision support
  In: Journal of Intelligent Information Systems, Vol. 27, No. 2: pp. 95-115
  
• Karimi, Iman; Hüllermeier, Eyke; Meskouris, Konstantin (2006)
  A fuzzy-probabilistic earthquake risk assessment system
  In: Soft Computing, Vol. 11, No. 3: pp. 229-238
  
• Bodenhofer, Ulrich; Hüllermeier, Eyke; Klawonn, Frank; Kruse, Rudolf (2006)
  Special Issue on Soft Computing for Information Mining. Editorial
  In: Soft Computing, Vol. 11, No. 5: pp. 397-399
  

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Paper

• Kasneci, Enkelejda; Seßler, Kathrin; Küchemann, Stefan; Bannert, Maria; Dementieva, Daryna; Fischer, Frank; Gasser, Urs; Groh, Georg; Günnemann, Stephan; Hüllermeier, Eyke; Krusche, Stephan; Kutyniok, Gitta; Michaeli, Tilman; Nerdel, Claudia; Pfeffer, Jürgen; Poquet, Oleksandra; Sailer, Michael; Schmidt, Albrecht; Seidel, Tina; Stadler, Matthias; Weller, Jochen; Kuhn, Jochen; Kasneci, Gjergji (2023)
  ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
  
  
• Heid, Stefan; Wever, Marcel Dominik; Hüllermeier, Eyke (2020)
  Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction
  
  
• Bode, Henrik; Heid, Stefan; Weber, Daniel; Hüllermeier, Eyke; Wallscheid, Oliver (2020)
  Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control
  
  
• El Mesaoudi-Paul, Adil; Bengs, Viktor; Hüllermeier, Eyke (2020)
  Online Preselection with Context Information under the Plackett-Luce Model
  
  
• Mohr, Felix; Wever, Marcel Dominik; Hüllermeier, Eyke (2018)
  Automated Machine Learning Service Composition
  
  
• Hüllermeier, Eyke (2017)
  From knowledge-based to data-driven modeling of fuzzy rule-based systems: A critical reflection
  
  
• Ahmadi Fahandar, Mohsen; Hüllermeier, Eyke (2017)
  Learning to Rank based on Analogical Reasoning
  
  

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Book Section

• Hanselle, Jonas; Tornede, Alexander; Wever, Marcel; Hüllermeier, Eyke (2021)
  Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data
  In: Karlapalem, Kamal; Cheng, Hong; Ramakrishnan, Naren; Agrawal, R. K.; Krishna Reddy, P.; Srivastava, Jaideep; Chakraborty, Tanmoy (eds.): Advances in Knowledge Discovery and Data Mining 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part I. Lecture Notes in Computer Science; Vol. 12712. Cham: Springer. pp. 152-163
  
• Rapp, Michael; Mencía, Eneldo Loza; Fürnkranz, Johannes; Nguyen, Vu-Linh; Hüllermeier, Eyke (2021)
  Learning Gradient Boosted Multi-label Classification Rules
  In: Hutter, Frank; Kersting, Kristian; Lijffijt, Jefrey; Valera, Isabel (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part III. Lecture Notes in Computer Science; Vol. 12459. Cham: Springer. pp. 124-140
  
• Tornede, Alexander; Wever, Marcel; Hüllermeier, Eyke (2020)
  Extreme Algorithm Selection with Dyadic Feature Representation
  In: Appice, Annalisa; Tsoumakas, Grigorios; Manolopoulos, Yannis; Matwin, Stan (eds.): Discovery Science. 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19–21, 2020, Proceedings. Lecture Notes in Computer Science; Vol. 12323. Cham: Springer. pp. 309-324
  
• El Mesaoudi-Paul, Adil; Weiß, Dimitri; Bengs, Viktor; Hüllermeier, Eyke; Tierney, Kevin (2020)
  Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach
  In: Kotsireas, Ilias S.; Pardalos, Panos M. (eds.): Learning and Intelligent Optimization. 14th International Conference, LION 14, Athens, Greece, May 24–28, 2020, Revised Selected Papers. Lecture Notes in Computer Science; Vol. 12096. Cham: Springer. pp. 216-232
  
• Wever, Marcel; Tornede, Alexander; Mohr, Felix; Hüllermeier, Eyke (2020)
  LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-label Classification
  In: Berthold, Michael; Feelders, Ad; Krempl, Georg (eds.): Advances in Intelligent Data Analysis XVIII. 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings. Lecture Notes in Computer Science; Vol. 12080. New York, NY: Association for Computing Machinery. pp. 561-573 (full text available)
  
• Brinker, Klaus; Hüllermeier, Eyke (2020)
  A Reduction of Label Ranking to Multiclass Classification
  In: (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part III. Lecture Notes in Computer Science; Vol. 11908. Cham: Springer. pp. 204-219
  
• Mohr, Felix; Wever, Marcel; Tornede, Alexander; Hüllermeier, Eyke (2019)
  From Automated to On-The-Fly Machine Learning
  In: David, Klaus; Geihs, Kurt; Lange, Martin; Stumme, Gerd (eds.): Informatik 2019. 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, Konferenzbeiträge, der 49. Jahrestagung der Gesellschaft für Informatik, 23.- 26.9.2019 Kassel, Deutschland. Bonn: Gesellschaft für Informatik. pp. 273-274
  
• Ahmadi Fahandar, Mohsen; Hüllermeier, Eyke (2019)
  Feature Selection for Analogy-Based Learning to Rank
  In: Kralj Novak, Petra; Šmuc, Tomislav; Džeroski, Sašo (eds.): Discovery Science. 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings. Lecture Notes in Computer Science; Vol. 11828. Cham: Springer. pp. 279-289
  
• Ahmadi Fahandar, Mohsen; Hüllermeier, Eyke (2019)
  Analogy-Based Preference Learning with Kernels
  In: Benzmüller, Christoph; Stuckenschmidt, Heiner (eds.): KI 2019: Advances in Artificial Intelligence. 42nd German Conference on AI, Kassel, Germany, September 23–26, 2019, Proceedings. Lecture Notes in Computer Science; Vol. 11793. Cham: Springer. pp. 34-47
  
• Hüllermeier, Eyke; Destercke, Sébastien; Couso, Ines (2019)
  Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants
  In: Ben Amor, Nahla; Quost, Benjamin; Theobald, Martin (eds.): Scalable Uncertainty Management. Lecture Notes in Computer Science; Vol. 11940. Cham: Springer. pp. 266-279
  
• Nguyen, Vu-Linh; Destercke, Sébastien; Hüllermeier, Eyke (2019)
  Epistemic Uncertainty Sampling
  In: Kralj Novak, Petra; Šmuc, Tomislav; Džeroski, Sašo (eds.): Discovery Science. 22nd International Conference, DS 2019, Split, Croatia, October 28–30, 2019, Proceedings. Lecture Notes in Computer Science; Vol. 11828. . pp. 72-86
  
• Mohr, Felix; Wever, Marcel; Hüllermeier, Eyke (2018)
  Reduction Stumps for Multi-class Classification
  In: Duivesteijn, Wouter; Siebes, Arno; Ukkonen, Antti (eds.): Advances in Intelligent Data Analysis XVII. 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings. Lecture Notes in Computer Science; Vol. 11191. Cham: Springer. pp. 225-237
  
• Schäfer, Dirk; Hüllermeier, Eyke (2018)
  Preference-Based Reinforcement Learning Using Dyad Ranking
  In: Soldatova, Larisa; Vanschoren, Joaquin; Papadopoulos, George; Ceci, Michelangelo (eds.): Discovery Science. Discovery Science 21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings. Lecture Notes in Computer Science; Vol. 11198. Cham: Springer. pp. 161-175
  
• Mencía, Eneldo Loza; Fürnkranz, Johannes; Hüllermeier, Eyke; Rapp, Michael (2018)
  Learning Interpretable Rules for Multi-Label Classification
  In: Jair Escalante, Hugo; Escalera, Sergio; Guyon, Isabelle; Baró, Xavier; Güçlütürk, Yağmur; Güçlü, Umut; Gerven, Marcel van (eds.): Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning; Cham: Springer. pp. 81-113
  
• Melnikov, Vitalik; Hüllermeier, Eyke (2017)
  Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics
  In: Mikut, Ralf; Hüllermeier, Eyke; Hoffmann, Frank (eds.): Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017. Karlsruhe: KIT Scientific Publishing. pp. 1-12
  
• Shaker, Ammar; Heldt, Waleri; Hüllermeier, Eyke (2017)
  Learning TSK Fuzzy Rules from Data Streams
  In: Ceci, Michelangelo; Hollmén, Jaakko; Džeroski, Sašo; Todorovsk, Ljupčo; Vens, Celine; Džeroski, Sašo (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II. Lecture Notes in Computer Science; Vol. 10535. . pp. 559-574
  
• Couso, Inés; Dubois, Didier; Hüllermeier, Eyke (2017)
  Maximum Likelihood Estimation and Coarse Data
  In: Moral, Serafín; Pivert, Olivier; Sánchez, Daniel; Marín, Nicolás (eds.): Scalable Uncertainty Management. 11th International Conference, SUM 2017, Granada, Spain, October 4-6, 2017, Proceedings. Lecture Notes in Computer Science; Vol. 10564. Cham: Springer. pp. 3-16
  
• Couso, Inés; Hüllermeier, Eyke (2017)
  Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators
  In: (eds.): Frontiers in Computational Intelligence. Studies in Computational Intelligence; Vol. 739. Cham: Springer. pp. 31-46
  
• Mohr, Felix; Lettmann, Theo; Hüllermeier, Eyke (2017)
  Planning with Independent Task Networks
  In: Kern-Isberner, Gabriele; Fürnkranz, Johannes; Thimm, Matthias (eds.): KI 2017: Advances in Artificial Intelligence. 40th Annual German Conference on AI, Dortmund, Germany, September 25–29, 2017, Proceedings. Lecture Notes in Computer Science; Vol. 10505. Cham: Springer. pp. 193-206
  
• Shabani, Aulon; Paul, Adil; Platon, Radu; Hüllermeier, Eyke (2016)
  Predicting the Electricity Consumption of Buildings: An Improved CBR Approach
  In: Goel, Ashok; Díaz-Agudo, M. Belén; Roth-Berghofer, Thomas (eds.): Case-Based Reasoning Research and Development. Lecture Notes in Computer Science; Vol. 9969. Cham: Springer. pp. 356-369
  
• Pfannschmidt, Karlson; Hüllermeier, Eyke; Held, Susanne; Neiger, Reto (2016)
  Evaluating Tests in Medical Diagnosis: Combining Machine Learning with Game-Theoretical Concepts
  In: Carvalho, Joao Paulo; Lesot, Marie-Jeanne; Kaymak, Uzay; Vieira, Susana; Bouchon-Meunier, Bernadette; Yager, Ronald R. (eds.): Information Processing and Management of Uncertainty in Knowledge-Based Systems. 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I. Communications in Computer and Information Science; Vol. 610. Cham: Springer. pp. 450-461
  
• Dembczyński, Krzysztof; Kotłowski, Wojciech; Waegeman, Willem; Busa-Fekete, Róbert; Hüllermeier, Eyke (2016)
  Consistency of Probabilistic Classifier Trees
  In: Frasconi, Paolo; Landwehr, Niels; Manco, Giuseppe; Vreeken, Jilles (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II. Lecture Notes in Computer Science; Vol. 9852. Cham: Springer. pp. 511-526
  
• Melnikov, Vitalik; Hüllermeier, Eyke (2016)
  Learning to Aggregate Using Uninorms
  In: Frasconi, Paolo; Landwehr, Niels; Manco, Giuseppe; Vreeken, Jilles (eds.): Machine Learning and Knowledge Discovery in Databases. Lecture Notes in Computer Science; Vol. 9852. . pp. 756-771
  
• Lu, Shenzhen; Hüllermeier, Eyke (2015)
  Locally weighted regression through data imprecisiation
  In: Hoffmann, Frank; Hüllermeier, Eyke (eds.): Proceedings. 25. Workshop Computational Intelligence, Dortmund, 26. - 27. November 2015. Schriftenreihe des Instituts für Angewandte Informatik - Automatisierungstechnik, Karlsruher Institut für Technologie; Vol. 54. Karlsruhe: KIT Scientific Publishing. pp. 97-103
  
• Ewerth, Ralph; Balz, Alexander; Gehlhaar, Jan; Dembczyński, Krzysztof; Hüllermeier, Eyke (2015)
  Depth Estimation in Monocular Images: Quantitative versus Qualitative Approaches
  In: Hoffmann, Frank; Hüllermeier, Eyke (eds.): Proceedings. 25. Workshop Computational Intelligence, Dortmund, 26. - 27. November 2015. Schriftenreihe des Instituts für Angewandte Informatik - Automatisierungstechnik, Karlsruher Institut für Technologie; Vol. 54. Karlsruhe: KIT Scientific Publishing. pp. 235-239
  
• Schäfer, Dirk; Hüllermeier, Eyke (2015)
  Dyad Ranking Using A Bilinear Plackett-Luce Model
  In: Appice, Annalisa; Pereira Rodrigues, Pedro; Santos Costa, Vítor; Gama, João; Jorge, Alípio; Soares, Carlos (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II. Lecture Notes in Computer Science; Vol. 9285. Cham: Springer. pp. 227-242
  
• Abdel-Aziz, Amira; Hüllermeier, Eyke (2015)
  Case Base Maintenance in Preference-Based CBR
  In: Hüllermeier, Eyke; Minor, Mirjam (eds.): Case-Based Reasoning Research and Development. 23rd International Conference, ICCBR 2015, Frankfurt am Main, Germany, September 28-30, 2015. Proceedings. Lecture Notes in Computer Science; Vol. 9343. Cham: Springer. pp. 1-14
  
• Hüllermeier, Eyke; Cheng, Weiwei (2015)
  Superset Learning Based on Generalized Loss Minimization
  In: (eds.): Machine Learning and Knowledge Discovery in Databases.European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II. Lecture Notes in Computer Science; Vol. 9285. Cham: Springer. pp. 260-275
  
• Henzgen, Sascha; Hüllermeier, Eyke (2015)
  Weighted Rank Correlation: A Flexible Approach Based on Fuzzy Order Relations
  In: (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II. Lecture Notes in Computer Science; Vol. 9285. . pp. 422-437
  
• Busa-Fekete, Róbert; Hüllermeier, Eyke (2014)
  A Survey of Preference-Based Online Learning with Bandit Algorithms
  In: Auer, Peter; Clark, Alexander; Zeugmann, Thomas; Zilles, Sandra (eds.): Algorithmic Learning Theory. 25th International Conference, ALT 2014, Bled, Slovenia, October 8-10, 2014. Proceedings. Lecture Notes in Computer Science; Vol. 8776. Cham: Springer. pp. 18-39
  
• Abdel-Aziz, Amira; Strickert, Marc; Hüllermeier, Eyke (2014)
  Learning Solution Similarity in Preference-Based CBR
  In: Lamontagne, Luc; Plaza, Enric (eds.): Case-Based Reasoning Research and Development. 22nd International Conference, ICCBR 2014, Cork, Ireland, September 29, 2014 - October 1, 2014. Proceedings. Lecture Notes in Computer Science; Vol. 8765. Cham: Springer. pp. 17-31
  
• Henzgen, Sascha; Hüllermeier, Eyke (2014)
  Mining Rank Data
  In: Džeroski, Sašo; Panov, Panče; Kocev, Dragi; Todorovski, Ljupčo (eds.): Discovery Science. 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014. Proceedings. Lecture Notes in Computer Science; Vol. 8777. Cham: Springer. pp. 123-134
  
• Henzgen, Sascha; Hüllermeier, Eyke (2013)
  Weighted Rank Correlation Measures Based on Fuzzy Order Relations
  In: Hoffmann, Frank; Hüllermeier, Eyke (eds.): Proceedings. 23. Workshop Computational Intelligence, Dortmund, 5. - 6. Dezember 2013. Schriftenreihe des Instituts für Angewandte Informatik - Automatisierungstechnik, Karlsruher Institut für Technologie; Vol. 46. Karlsruhe: KIT Scientific Publishing. pp. 227-236
  
• Fober, Thomas; Klebe, Gerhard; Hüllermeier, Eyke (2013)
  Local Clique Merging: An Extension of the Maximum Common Subgraph Measure with Applications in Structural Bioinformatics
  In: Lausen, Berthold; Poel, Dirk van den; Ultsch, Alfred (eds.): Algorithms from and for Nature and Life. Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization; Cham: Springer. pp. 279-286
  
• Hüllermeier, Eyke; Tehrani, Ali Fallah (2013)
  Efficient Learning of Classifiers Based on the 2-Additive Choquet Integral
  In: Moewes, Christian; Nürnberger, Andreas (eds.): Computational Intelligence in Intelligent Data Analysis. Studies in Computational Intelligence; Vol. 445. Berlin, Heidelberg: Springer. pp. 17-29
  
• Hüllermeier, Eyke; Cheng, Weiwei (2013)
  Preference-Based CBR: General Ideas and Basic Principles
  In: Rossi, Francesca (eds.): Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, Beijing, China, 3 - 9 August 2013, Vol. 4. Palo Alto, Calif.: AAAI Press. pp. 3012-3016
  
• Shaker, Ammar; Hüllermeier, Eyke (2013)
  Recovery Analysis for Adaptive Learning from Non-stationary Data Streams
  In: Burduk, Robert; Jackowski, Konrad; Kurzynski, Marek; Wozniak, Michał; Zolnierek, Andrzej (eds.): Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing; Vol. 226. . pp. 289-298
  
• Henzgen, Sascha; Strickert, Marc; Hüllermeier, Eyke (2013)
  Rule Chains for Visualizing Evolving Fuzzy Rule-Based Systems
  In: Burduk, Robert; Jackowski, Konrad; Kurzynski, Marek; Wozniak, Michał; Zolnierek, Andrzej (eds.): Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing; Vol. 226. . pp. 279-288
  
• Senge, Robin; Del Coz, Juan José; Hüllermeier, Eyke (2013)
  On the Problem of Error Propagation in Classifier Chains for Multi-label Classification
  In: Spiliopoulou, Myra; Schmidt-Thieme, Lars; Janning, Ruth (eds.): Data Analysis, Machine Learning and Knowledge Discovery. Studies in Classification, Data Analysis, and Knowledge Organization; Cham: Springer. pp. 163-170
  
• Dembczyński, Krzysztof; Waegeman, Willem; Hüllermeier, Eyke (2012)
  An Analysis of Chaining in Multi-Label Classification
  In: De Raedt, Luc; Bessiere, Christian; Dubois, Didier; Doherty, Patrick; Frasconi, Paolo; Heintz, Fredrik; Lucas, Peter (eds.): ECAI 2012 : 20th European Conference on Artificial Intelligence, 27 - 31 August 2012, Montpellier, France. Frontiers in Artificial Intelligence and Applications; Vol. 242. Amsterdam: IOS Press. pp. 294-299 (full text available)
  
• Hüllermeier, Eyke (2012)
  Fuzzy Rules in Data Mining: From Fuzzy Associations to Gradual Dependencies
  In: Trillas, Enric; Bonissone, Piero P.; Magdalena, Luis; Kacprz, Janusz (eds.): Combining Experimentation and Theory. A Hommage to Abe Mamdani. Studies in Fuzziness and Soft Computing; Vol. 271. . pp. 123-135 (full text available)
  
• Hüllermeier, Eyke; Fallah Tehrani, Ali (2012)
  On the VC-Dimension of the Choquet Integral
  In: Greco, Salvatore; Bouchon-Meunier, Bernadette; Coletti, Gulianella; Fedrizzi, Mario; Matarazzo, Benedetto; Yager, Ronald R. (eds.): Advances on Computational Intelligence. 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, Catania, Italy, July 9-13, 2012. Proceedings, Part I. Communications in Computer and Information Science; Vol. 297. Berlin, Heidelberg: Springer. pp. 42-50
  
• Cheng, Weiwei; Hüllermeier, Eyke (2012)
  Probability Estimation for Multi-class Classification Based on Label Ranking
  In: Flach, Peter A.; Bie, Tijl De; Cristianini, Nello (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II. Lecture Notes in Computer Science; Vol. 7524. Berlin, Heidelberg: Springer. pp. 83-98
  
• Hüllermeier, Eyke; Schlegel, Patrice (2011)
  Preference-Based CBR: First Steps toward a Methodological Framework
  In: Ram, Ashwin; Wiratunga, Nirmalie (eds.): Case-Based Reasoning Research and Development. 19th International Conference on Case-Based Reasoning, ICCBR 2011, London, UK, September 12-15, 2011. Proceedings. Lecture Notes in Computer Science; Vol. 6880. Berlin, Heidelberg: Springer. pp. 77-91
  
• Hüllermeier, Eyke; Fürnkranz, Johannes (2011)
  Learning from Label Preferences
  In: Elomaa, Tapio; Hollmén, Jaakko; Mannila, Heikki (eds.): Discovery Science. 14th International Conference, DS 2011, Espoo, Finland, October 5-7, 2011. Proceedings. Lecture Notes in Computer Science; Vol. 6926. . pp. 2-17
  
• Cheng, Weiwei; Fürnkranz, Johannes; Hüllermeier, Eyke; Park, Sang-Hyeun (2011)
  Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning
  In: Gunopulos, Dimitrios; Hofmann, Thomas; Malerba, Donato; Vazirgiannis, Michalis (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011. Proceedings, Part I. Lecture Notes in Computer Science; Vol. 6911. Berlin, Heidelberg: Springer. pp. 312-327
  
• Fürnkranz, Johannes; Hüllermeier, Eyke (2010)
  Preference Learning: An Introduction
  In: Fürnkranz, Johannes; Hüllermeier, Eyke (eds.): Preference Learning. Berlin: Springer. pp. 1-17
  
• Fürnkranz, Johannes; Hüllermeier, Eyke (2010)
  Preference Learning and Ranking by Pairwise Comparison
  In: Fürnkranz, Johannes; Hüllermeier, Eyke (eds.): Preference Learning. Berlin, Heidelberg: Springer. pp. 65-82
  
• Hühn, Jens Christian; Hüllermeier, Eyke (2010)
  An Analysis of the FURIA Algorithm for Fuzzy Rule Induction
  In: Koronacki, Jacek; Raś, Zbigniew W.; Wierzchoń, Sławomir T.; Kacprzyk, Janusz (eds.): Advances in Machine Learning I. Dedicated to the Memory of Professor Ryszard S. Michalski. Studies in Computational Intelligence; Vol. 262. Berlin, Heidelberg: Springer. pp. 321-344
  
• Cheng, Weiwei; Rademaker, Michaël; De Baets, Bernard; Hüllermeier, Eyke (2010)
  Predicting Partial Orders: Ranking with Abstention
  In: Balcázar, José Luis; Bonchi, Francesco; Gionis, Aristides; Sebag, Michèle (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part I. Lecture Notes in Computer Science; Vol. 6321. Berlin, Heidelberg: Springer. pp. 215-230
  
• Dembczyński, Krzysztof; Waegeman, Willem; Cheng, Weiwei; Hüllermeier, Eyke (2010)
  Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss
  In: Balcázar, José Luis; Bonchi, Francesco; Gionis, Aristides; Sebag, Michèle (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part I. Lecture Notes in Computer Science; Vol. 6321. Berlin, Heidelberg: Springer. pp. 280-295
  
• Hüllermeier, Eyke (2010)
  Uncertainty in Clustering and Classification
  In: Deshpande, Amol; Hunter, Anthony (eds.): Scalable Uncertainty Management.4th International Conference, SUM 2010, Toulouse, France, September 27-29, 2010. Proceedings. Lecture Notes in Computer Science; Vol. 6379. Berlin, Heidelberg: Springer. pp. 16-19
  
• Koh, Hyung-Won; Hüllermeier, Eyke (2010)
  Mining Gradual Dependencies Based on Fuzzy Rank Correlation
  In: Borgel, Christian (eds.): Combining Soft Computing and Statistical Methods in Data Analysis. Advances in Intelligent and Soft Computing; Vol. 77. Berlin, Heidelberg: Springer. pp. 379-386
  
• Fürnkranz, Johannes; Hüllermeier, Eyke; Vanderlooy, Stijn (2009)
  Binary Decomposition Methods for Multipartite Ranking
  In: Buntine, Wray; Grobelnik, Marko; Mladenić, Dunja; Shawe-Taylor, John (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I. Lecture Notes in Computer Science; Vol. 5781. Berlin, Heidelberg: Springer. pp. 359-374
  
• Hüllermeier, Eyke (2009)
  On the Usefulness of Fuzzy Sets in Data Mining
  In: (eds.): Views on Fuzzy Sets and Systems from Different Perspectives. Philosophy and Logic, Criticisms and Applications. Studies in Fuzziness and Soft Computing; Vol. 243. Berlin, Heidelberg: Springer. pp. 457-470
  
• Cheng, Weiwei; Hüllermeier, Eyke (2009)
  A New Instance-Based Label Ranking Approach Using the Mallows Model
  In: Yu, Wen; He, Haibo; Zhang, Nian (eds.): Advances in Neural Networks – ISNN 2009 : 6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part I. Lecture Notes in Computer Science; Vol. 5551. Berlin, Heidelberg: Springer. pp. 707-716
  
• Cheng, Weiwei; Hüllermeier, Eyke (2009)
  Combining Instance-Based Learning and Logistic Regression for Multilabel Classification
  In: Buntine, Wray; Grobelnik, Marko; Mladenić, Dunja; Shawe-Taylor, John (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I. Lecture Notes in Computer Science; Vol. 5781. Berlin, Heidelberg: Springer. pp. 6-6
  
• Hüllermeier, Eyke (2008)
  Granular Computing in Machine Learning and Data Mining
  In: Pedrycz, Witold; Skowron, Andrzej; Kreinovich, Vladik (eds.): Handbook of Granular Computing. . pp. 889-906
  
• Hüllermeier, Eyke; Fürnkranz, Johannes (2008)
  Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants
  In: Della Riccia, Giacomo; Dubois, Didier; Kruse, Rudolf; Lenz, Hans-Joachim (eds.): Preferences and Similarities. CISM International Centre for Mechanical Sciences; Vol. 504. Vienna: Springer. pp. 283-304
  
• Cheng, Weiwei; Hüllermeier, Eyke (2008)
  Learning Similarity Functions from Qualitative Feedback
  In: Althoff, Klaus-Dieter; Bergmann, Ralph; Minor, Mirjam; Hanft, Alexandre (eds.): Advances in Case-Based Reasoning. 9th European Conference, ECCBR 2008, Trier, Germany, September 1-4, 2008. Proceedings. Lecture Notes in Computer Science; Vol. 5239. Berlin, Heidelberg: Springer. pp. 120-134
  
• Hüllermeier, Eyke; Vladimirskiy, Ilya; Prados Suárez, Belén; Stauch, Eva (2008)
  Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions
  In: Althoff, Klaus-Dieter; Bergmann, Ralph; Minor, Mirjam; Hanft, Alexandre (eds.): Advances in Case-Based Reasoning. Lecture Notes in Computer Science. 9th European Conference, ECCBR 2008, Trier, Germany, September 1-4, 2008. Proceedings; Vol. 5239. Berlin, Heidelberg: Springer. pp. 240-254
  
• Vanderlooy, Stijn; Hüllermeier, Eyke (2008)
  A Critical Analysis of Variants of the AUC
  In: Daelemans, Walter; Goethals, Bart; Morik, Katharina (eds.): Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I. Lecture Notes in Computer Science; Vol. 5211. Berlin, Heidelberg: Springer. pp. 13-13
  
• Hüllermeier, Eyke (2008)
  Why Fuzzy Set Theory is Useful in Data Mining
  In: Poncelet, Pascal; Masseglia, Florent; Teisseire, Maguelonne (eds.): Successes and New Directions in Data Mining. Hershey ; New York: Information Science Reference. pp. 1-16
  
• Hüllermeier, Eyke (2008)
  Fuzzy Methods for Data Mining and Machine Learning: State of the Art and Prospects
  In: Bustince, Humberto; Herrera, Francisco; Montero, Javier (eds.): Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Studies in Fuzziness and Soft Computing; Vol. 220. Berlin, Heidelberg: Springer. pp. 357-375
  
• Beringer, Jürgen; Hüllermeier, Eyke (2007)
  An Efficient Algorithm for Instance-Based Learning on Data Streams
  In: Perner, Petra (eds.): Advances in Data Mining. Theoretical Aspects and Applications. 7th Industrial Conference, ICDM 2007, Leipzig, Germany, July 14-18, 2007. Proceedings. Lecture Notes in Computer Science; Vol. 4597. Berlin, Heidelberg: Springer. pp. 34-48
  
• Sulzmann, Jan-Nikolas; Fürnkranz, Johannes; Hüllermeier, Eyke (2007)
  On Pairwise Naive Bayes Classifiers
  In: Kok, Joost N.; Koronacki, Jacek; Lopez de Mantaras, Raomon; Matwin, Stan; Mladenič, Dunja; Skowron, Andrzej (eds.): Machine Learning: ECML 2007. 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007. Proceedings. Lecture Notes in Computer Science; Vol. 4701. Berlin, Heidelberg: Springer. pp. 371-381
  
• Beringer, Jürgen; Hüllermeier, Eyke (2007)
  Fuzzy Clustering of Parallel Data Streams
  In: Oliveira, Jose Valente de; Pedrycz, Witold (eds.): Advances in Fuzzy Clustering and its Applications. Chichester: Wiley. pp. 333-352
  
• Hüllermeier, Eyke; Fürnkranz, Johannes (2007)
  On Minimizing the Position Error in Label Ranking
  In: Kok, Joost N.; Koronacki, Jacek; Lopez de Mantaras, Raomon; Matwin, Stan; Mladenič, Dunja; Skowron, Andrzej (eds.): Machine Learning: ECML 2007. 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007. Proceedings. Lecture Notes in Computer Science; Vol. 4701. Berlin, Heidelberg: Springer. pp. 583-590
  
• Brinker, Klaus; Hüllermeier, Eyke (2007)
  Label Ranking in Case-Based Reasoning
  In: Weber, Rosina O.; Richter, Michael M. (eds.): Case-Based Reasoning Research and Development. 7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast, Northern Ireland, UK, August 13-16, 2007 Proceedings. Lecture Notes in Computer Science; Vol. 4626. Berlin, Heidelberg: Springer. pp. 77-91
  
• Hüllermeier, Eyke (2006)
  The Choquet-Integral as an Aggregation Operator in Case-Based Learning
  In: Reusch, Bernd (eds.): Computational Intelligence, Theory and Applications. International Conference 9th Fuzzy Days in Dortmund, Germany, Sept. 18–20, 2006 Proceedings. Berlin, Heidelberg: Springer. pp. 615-627
  
• Brinker, Klaus; Hüllermeier, Eyke (2006)
  Case-Based Label Ranking
  In: Fürnkranz, Johannes; Scheffer, Tobias; Spiliopoulou, Myra (eds.): Machine Learning: ECML 2006. 17th European Conference on Machine Learning Berlin, Germany, September 18-22, 2006 Proceedings. Lecture Notes in Computer Science; Vol. 4212. Berlin, Heidelberg: Springer. pp. 566-573
  
• Hüllermeier, Eyke; Fürnkranz, Johannes (2005)
  Learning Label Preferences: Ranking Error Versus Position Error
  In: Fazel Famili, A.; Kok, Joost N.; Peña, José M.; Siebes, Arno; Feelders, Ad (eds.): Advances in Intelligent Data Analysis VI. 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005. Proceedings. Lecture Notes in Computer Science; Vol. 3646. Berlin, Heidelberg: Springer. pp. 180-191
  
• Hüllermeier, Eyke; Beringer, Jürgen (2005)
  Learning from Ambiguously Labeled Examples
  In: Famili, A. Fazel; Kok, Joost N.; Peña, José M.; Siebes, Arno; Feelders, Ad (eds.): Advances in Intelligent Data Analysis VI. Lecture Notes in Computer Science. 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005. Proceedings; Vol. 3646. Berlin, Heidelberg: Springer. pp. 168-179
  
• Dubois, Didier; Hüllermeier, Eyke (2005)
  A Notion of Comparative Probabilistic Entropy Based on the Possibilistic Specificity Ordering
  In: (eds.): Symbolic and Quantitative Approaches to Reasoning with Uncertainty. 8th European Conference, ECSQARU 2005, Barcelona, Spain, July 6-8, 2005. Proceedings. Lecture Notes in Computer Science; Vol. 3571. Berlin, Heidelberg: Springer. pp. 848-859
  
• Hüllermeier, Eyke (2005)
  Fuzzy Methods in Knowledge Discovery
  In: Reusch, Bernd (eds.): Computational Intelligence, Theory and Applications. International Conference 8th Fuzzy Days in Dortmund, Germany, Sept. 29–Oct. 01, 2004 Proceedings. Advances in Soft Computing; Vol. 33. Berlin, Heidelberg: Springer. pp. 483-483
  
• Fürnkranz, Johannes; Hüllermeier, Eyke (2003)
  Pairwise Preference Learning and Ranking
  In: Lavrač, Nada; Gamberger, Dragan; Blockeel, Hendrik; Todorovski, Ljupčo (eds.): Machine Learning: ECML 2003. 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003. Proceedings. Lecture Notes in Computer Science; Vol. 2837. Berlin, Heidelberg: Springer. pp. 145-156
  
• Hüllermeier, Eyke (2003)
  Instance-Based Learning of Credible Label Sets
  In: Günter, Andreas; Kruse, Rudolf; Neumann, Bernd (eds.): KI 2003: Advances in Artificial Intelligence. 26th Annual German Conference on AI, KI 2003, Hamburg, Germany, September 15-18, 2003. Proceedings. Lecture Notes in Computer Science; Vol. 2821. Berlin, Heidelberg: Springer. pp. 450-464
  
• Hüllermeier, Eyke (2003)
  Regularized Learning with Flexible Constraints
  In: Berthold, Michael R.; Lenz, Hans-Joachim; Bradley, Elizabeth; Kruse, Rudolf; Borgelt, Christian (eds.): Advances in Intelligent Data Analysis V. 5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003. Proceedings. Lecture Notes in Computer Science; Vol. 2810. Berlin, Heidelberg: Springer. pp. 13-24
  
• Dubois, Didier; Hüllermeier, Eyke; Prade, Henri (2003)
  Flexible Control of Case-Based Prediction in the Framework of Possibility Theory
  In: Blanzieri, Enrico; Portinale, Luigi (eds.): Advances in Case-Based Reasoning. 5th European Workshop, EWCBR 2000 Trento, Italy, September 6–9, 2000 Proceedings. Lecture Notes in Computer Science; Vol. 1898. Berlin, Heidelberg: Springer. pp. 61-73
  
• Hüllermeier, Eyke (2003)
  A Method for Predicting Solutions in Case-Based Problem Solving
  In: Blanzieri, Enrico; Portinale, Luigi (eds.): Advances in Case-Based Reasoning. 5th European Workshop, EWCBR 2000 Trento, Italy, September 6–9, 2000 Proceedings. Lecture Notes in Computer Science; Vol. 1898. Berlin, Heidelberg: Springer. pp. 124-135
  
• Hüllermeier, Eyke (2003)
  Inducing Fuzzy Concepts through Extended Version Space Learning
  In: Bilgiç, Taner; De Baets, Bernard; Kaynak, Okyay (eds.): Fuzzy Sets and Systems — IFSA 2003. 10th International Fuzzy Systems Association World Congress Istanbul, Turkey, June 30 – July 2, 2003 Proceedings. Lecture Notes in Computer Science; Vol. 2715. Berlin, Heidelberg: Springer. pp. 677-684
  
• Dubois, Didier; Hüllermeier, Eyke; Prade, Henri (2003)
  A Note on Quality Measures for Fuzzy Association Rules
  In: Bilgiç, Taner; De Baets, Bernard; null, Okyay Kaynak Taner BilgiçBernard De BaetsOkyay Kaynak (eds.): Fuzzy Sets and Systems — IFSA 2003. 10th International Fuzzy Systems Association World Congress Istanbul, Turkey, June 30 – July 2, 2003 Proceedings. Lecture Notes in Computer Science; Vol. 2715. Berlin, Heidelberg: Springer. pp. 346-353
  
• Hüllermeier, Eyke (2003)
  Sequential Decision Making in Heuristic Search
  In: Della Riccia, Giacomo; Dubois, Didier; Kruse, Rudolf; Lenz, Hans-J. (eds.): Planning Based on Decision Theory. International Centre for Mechanical Sciences; Vol. 472. Vienna: Springer. pp. 27-41
  
• Dubois, Didier; Hüllermeier, Eyke; Prade, Henri (2003)
  Possibilistic case-based decisions
  In: Lesage, Cédric; Cottrell, Marie (eds.): Connectionist Approaches in Economics and Management Sciences. Advances in Computational Management Science; Vol. 6. Boston, MA: Springer. pp. 31-48
  
• Hüllermeier, Eyke (2002)
  Experience-Based Decision Making and Learning from Examples
  In: (eds.): Operations Research Proceedings 2001. Selected Papers of the International Conference on Operations Research (OR 2001) Duisburg, September 3–5, 2001. Berlin, Heidelberg: Springer. pp. 363-370
  
• Hüllermeier, Eyke (2002)
  Exploiting similarity and experience in decision making
  In: (eds.): Proceedings of the 2002 IEEE International Conference on Fuzzy Systems: May 12 - 17, 2002, Hilton Hawaiian Village Hotel, Honolulu, Hawaii. Vol. 1. Piscataway, NJ: IEEE. pp. 729-734
  
• Hüllermeier, Eyke (2002)
  Association Rules for Expressing Gradual Dependencies
  In: Elomaa, Tapio; Mannila, Heikki; Toivonen, Hannu (eds.): Principles of Data Mining and Knowledge Discovery. 6th European Conference, PKDD 2002 Helsinki, Finland, August 19–23, 2002 Proceedings. Lecture Notes in Computer Science; Vol. 2431. Berlin, Heidelberg: Springer. pp. 200-211
  
• Hüllermeier, Eyke; Dubois, Didier; Prade, Henri (2002)
  Knowledge-Based Extrapolation of Cases: A Possibilistic Approach
  In: Bouchon-Meunier, Bernadette; Gutiérrez-Ríos, Julio; Magdalena, Luis; Yager, Ronald R. (eds.): Technologies for Constructing Intelligent Systems 1. Studies in Fuzziness and Soft Computing; Vol. 89. Heidelberg: Physica Verlag. pp. 377-390
  
• Hüllermeier, Eyke (2002)
  Possibilistic Induction in Decision-Tree Learning
  In: Elomaa, Tapio; Mannila, Heikki; Toivonen, Hannu (eds.): Machine Learning: ECML 2002.13th European Conference on Machine Learning Helsinki, Finland, August 19–23, 2002 Proceedings. Lecture Notes in Computer Science; Vol. 2430. Cham: Springer. pp. 173-184
  
• Hüllermeier, Eyke (2001)
  Fuzzy Association Rules: Semantic Issues and Quality Measures
  In: Reusch, Bernd (eds.): Computational Intelligence. Theory and Applications. International Conference, 7th Fuzzy Days Dortmund, Germany, October 1–3, 2001 Proceedings. Lecture Notes in Computer Science; Vol. 2206. Berlin, Heidelberg: Springer. pp. 380-391
  
• Hüllermeier, Eyke (2001)
  Implication-Based Fuzzy Association Rules
  In: (eds.): Principles of Data Mining and Knowledge Discovery. 5th European Conference, PKDD 2001, Freiburg, Germany, September 3–5, 2001 Proceedings. Lecture Notes in Computer Science; Vol. 2168. Berlin, Heidelberg: Springer. pp. 241-252
  
• Hüllermeier, Eyke (1999)
  A Possibilistic Formalization of Case-Based Reasoning and Decision Making
  In: Reusch, Bernd (eds.): Computational Intelligence. Theory and Applications International Conference, 6th Fuzzy Days Dortmund, Germany, May 25–28 1999 Proceedings. Lecture Notes in Computer Science; Vol. 1625. Berlin, Heidelberg: Springer. pp. 411-420
  
• Hüllermeier, Eyke (1999)
  Exploiting Similarity for Supporting Data Analysis and Problem Solving
  In: Hand, David J.; Kok, Joost N.; Berthold, Michael R. (eds.): Advances in Intelligent Data Analysis. Third International Symposium, IDA-99 Amsterdam, The Netherlands, August 9–11, 1999 Proceedings. Lecture Notes in Computer Science; Vol. 1642. Berlin, Heidelberg: Springer. pp. 257-268
  

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Encyclopedia article

• Fürnkranz, Johannes; Hüllermeier, Eyke (2017)
  Preference Learning
  In: Sammut, Claude; Webb, Geoffrey I. (eds.): Encyclopedia of Machine Learning and Data Mining. Boston, MA: Springer. pp. 1000-1005
  
• Fürnkranz, Johannes; Hüllermeier, Eyke (2016)
  Preference Learning
  In: Phung, Dinh; Webb, Geoffrey I.; Sammut, Claude (eds.): Encyclopedia of Machine Learning and Data Mining. New York, NY: Springer. pp. 1-7
  
• Fürnkranz, Johannes; Hüllermeier, Eyke (2012)
  Preference Learning
  In: Seel, N. M. (eds.): Encyclopedia of the Sciences of Learning. Boston, MA: Springer
  
• Fürnkranz, Johannes; Hüllermeier, Eyke (2011)
  Preference Learning
  In: Sammut, Claude (eds.): Encyclopedia of Machine Learning. Boston, MA: Springer. pp. 789-795
  

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Conference Item

• Damke, Clemens; Hüllermeier, Eyke (2024)
  CUQ-GNN: Committee-Based Graph Uncertainty Quantification Using Posterior Networks
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 9. - 13. September 2024, Vilnius, Lithuania
  
• Vahidi, Amihossein; Wimmer, Lisa; Gündüz, Hüseyin Anil; Bischl, Bernd; Hüllermeier, Eyke; Rezaei, Mina (2024)
  Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 9. - 13. September 2024, Vilnius, Lithuania
  
• Löhr, Timo; Ingrisch, Michael; Hüllermeier, Eyke (2024)
  Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification
  22nd International Conference of Artificial Intelligence in Medicine (AIME 2024), 9. - 12. July 2024, Salt Lake City, Utah, USA
  
• Juergens, Mira; Meinert, Nis; Bengs, Viktor; Hüllermeier, Eyke; Waegeman, Willem (2024)
  Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
  41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria (full text available)
  
• Fumagalli, Fabian; Muschalik, Maximilian; Kolpaczki, Patrick; HÜllermeier, Eyke (2024)
  KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
  41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria (full text available)
  
• Herrmann, Moritz; Lange, F. Julian D.; Eggensperger, Katharina; Casalicchio, Giuseppe; Wever, Marcel; Feurer, Matthias; Rügamer, David; Hüllermeier, Eyke; Boulesteix, Anne-Laure; Bischl, Bernd (2024)
  Position: Why We Must Rethink Empirical Research in Machine Learning
  41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria (full text available)
  
• Yusuf, Sale; Bengs, Viktor; Caprio, Michele; Hüllermeier, Eyke (2024)
  Second-Order Uncertainty Quantification: A Distance-Based Approach
  41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria (full text available)
  
• Bengs, Viktor; Haddenhorst, Björn; Hüllermeier, Eyke (2024)
  Identifying Copeland Winners in Dueling Bandits with Indifferences
  27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2. - 4. May 2024, Valencia, Spain (full text available)
  
• Vahidi, Amirhossein; Schosser, Simon; Wimmer, Lisa; Li, Yawei; Bischl, Bernd; Hüllermeier, Eyke; Rezaei, Mina (2024)
  Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization
  12th International Conference on Learning Representations (ICLR 2024), 7. - 11. May 2024, Vienna, Austria (full text available)
  
• Kolpaczki, Patrick; Muschalik, Maximilian; Fumagalli, Fabian; Hammer, Barbara; Hüllermeier, Eyke (2024)
  SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification
  27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2. - 4. May 2024, Valencia, Spain (full text available)
  
• Muschalik, Maximilian; Fumagalli, Fabian; Hammer, Barbara; Hüllermeier, Eyke (2024)
  Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
  AAAI Conference on Artificial Intelligence 2024, 20-27 February 2024, Vancouver, Canada
  
• Lienen, Julian; Hüllermeier, Eyke (2024)
  Mitigating Label Noise through Data Ambiguation
  AAAI Conference on Artificial Intelligence 2024, 20-27 February 2024, Vancouver, Canada
  
• Kolpaczki, Patrick; Bengs, Viktor; Muschalik, Maximilian; Hüllermeier, Eyke (2024)
  Approximating the Shapley Value without Marginal Contributions
  AAAI Conference on Artificial Intelligence 2024, 20-27 February 2024, Vancouver, Canada
  
• Bevanda, Petar; Beier, Max; Lederer, Armin; Sosnowski, Stefan; Hüllermeier, Eyke; Hirche, Sandra (2023)
  Koopman Kernel Regression
  37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), 10. - 16. December 2023, New Orleans, Louisiana, USA (full text available)
  
• Fumagalli, Fabian; Muschalik, Maximilian; Kolpaczki, Patrick; Hüllermeier, Eyke (2023)
  SHAP-IQ: Unified Approximation of any-order Shapley Interactions
  37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), 10. - 16. December 2023, New Orleans, Louisiana, USA (full text available)
  
• Fumagalli, Fabian; Muschalik, Maximilian; Hüllermeier, Eyke; Hammer, Barbara (2023)
  On Feature Removal for Explainability in Dynamic Environments
  ESANN 2023 - European Symposium on Artificial Neural Networks, 4-6 October 2023, Bruges, Belgium
  
• Hanselle, Jonas; Kornowicz, Jaroslaw; Heid, Stefan; Thommes, Kirsten; Hüllermeier, Eyke (2023)
  Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain
  Lernen, Wissen, Daten, Analysen (LWDA), 9-11 October 2023, Marburg, Germany
  
• Brandt, Jasmin; Schede, Elias; Sharma, Shivam; Bengs, Viktor; Hüllermeier, Eyke; Tierney, Kevin (2023)
  Contextual Preselection Methods in Pool-based Realtime Algorithm Configuration
  Lernen, Wissen, Daten, Analysen (LWDA), 9-11 October 2023, Marburg, Germany
  
• Haas, Stefan; Hüllermeier, Eyke (2023)
  Rectifying Bias in Ordinal Observational Data Using Unimodal Label Smoothing
  Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 18-22 September, 2023, Torino, Italy
  
• Muschalik, Maximilian; Fumagalli, Fabian; Hammer, Barbara; Hüllermeier, Eyke (2023)
  iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams
  Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 18-22 September, 2023, Torino, Italy
  
• Lienen, Julian; Demir, Caglar; Hüllermeier, Eyke (2023)
  Conformal Credal Self-Supervised Learning
  Twelfth Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023), September 13-15, 2023, Limassol, Cyprus
  
• Javanmardi, Alireza; Sale, Yusuf; Hofman, Paul; Hüllermeier, Eyke (2023)
  Conformal Prediction with Partially Labeled Data
  Twelfth Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023), September 13-15, 2023, Limassol, Cyprus
  
• Schede, Elias; Brandt, Jasmin; Tornede, Alexander; Wever, Marcel; Bengs, Viktor; Hüllermeier, Eyke; Tierney, Kevin (2023)
  A Survey of Methods for Automated Algorithm Configuration (Extended Abstract)
  Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI 2023), 19-25 August 2023, Macao, S.A.R
  
• Caprio, Michele; Sale, Yusuf; Hüllermeier, Eyke; Lee, Insup (2023)
  A Novel Bayes’ Theorem for Upper Probabilities
  Epi UAI 2023 - First International Workshop on Epistemic Uncertainty in Artificial Intelligence, August 4, 2023, Pittsburgh, PA, USA
  
• Sale, Yusuf; Caprio, Michele; Hüllermeier, Eyke (2023)
  Is the volume of a credal set a good measure for epistemic uncertainty?
  Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), 1-3 August, 2023, Pittsburgh, PA, USA
  
• Belaid, Mohamed Karim; Bornemann, Richard; Rabus, Maximilian; Krestel, Ralf; Hüllermeier, Eyke (2023)
  Compare-xAI: Toward Unifying Functional Testing Methods for Post-hoc XAI Algorithms into a Multi-dimensional Benchmark
  World Conference on Explainable Artificial Intelligence (xAI 2023), 26-28 July 2023, Lisboa, Portugal
  
• Muschalik, Maximilian; Fumagalli, Fabian; Jagtani, Rohit; Hammer, Barbara; Hüllermeier, Eyke (2023)
  iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios
  World Conference on Explainable Artificial Intelligence (xAI 2023), 26-28 July 2023, Lisboa, Portugal
  
• Wickert, Anna-Katharina; Damke, Clemens; Baumgärtner, Lars; Hüllermeier, Eyke; Mezini, Mira (2023)
  UnGoML: Automated Classification of unsafe Usages in Go
  20th International Conference on Mining Software Repositories (MSR), 15-16 May, 2023, Melbourne, Australia
  
• Nguyen, Duc Anh; Levie, Ron; Lienen, Julian; Hüllermeier, Eyke; Kutyniok, Gitta (2023)
  Memorization-Dilation: Modeling Neural Collapse Under Noise
  The Eleventh International Conference on Learning Representations, 1-5 May, 2023, Kigali, Rwanda
  
• Mortier, Thomas; Bengs, Viktor; Hüllermeier, Eyke; Luca, Stijn; Waegeman, Willem (2023)
  On the Calibration of Probabilistic Classifier Sets
  26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), 25-27 April, 2023, Valencia, Spain
  
• Brandt, Jasmin; Schede, Elias; Haddenhorst, Björn; Bengs, Viktor; Hüllermeier, Eyke; Tierney, Kevin (2023)
  AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration
  AAAI Conference on Artificial Intelligence, February, 2023, Washington, DC, USA
  
• Sharma, Arnab; Melnikov, Vitalik; Hüllermeier, Eyke; Wehrheim, Heike (2023)
  Property-Driven Black-Box Testing of Numeric Functions
  Software Engineering 2023, 20-24 February 2023, Paderborn, Germany (full text available)
  
• Gupta, Pritha; Drees, Jan Peter; Hüllermeier, Eyke (2023)
  Automated Side-Channel Attacks using Black-Box Neural Architecture Search
  18th International Conference on Availability, Reliability and Security, 29 August - 1 September 2023, Benevento, Italy
  
• Hanselle, Jonas; Fürnkranz, Johannes; Hüllermeier, Eyke (2023)
  Probabilistic Scoring Lists for Interpretable Machine Learning
  26th International Conference on Discovery Science (DS 2023), October 9-11, 2023, Porto, Portugal
  
• Wever, Marcel; Özdogan, Miran; Hüllermeier, Eyke (2023)
  Cooperative Co-Evolution for Ensembles of Nested Dichotomies for Multi-Class Classification
  Genetic and Evolutionary Computation Conference (GECCO '23), July 15-19, 2023, Lisbon, Portugal
  
• Bengs, Viktor; Hüllermeier, Eyke; Waegeman, Willem (2023)
  On Second-Order Scoring Rules for Epistemic Uncertainty Quantification
  40th International Conference on Machine Learning (ICML 2023), 23-29 July, 2023, Hawaii, USA
  
• Wimmer, Lisa; Sale, Yusuf; Hofman, Paul; Bischl, Bernd; Hüllermeier, Eyke (2023)
  Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
  Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), 1-3 August, 2023, Pittsburgh, PA, USA
  
• Bengs, Viktor; Hüllermeier, Eyke; Waegeman, Willem (2022)
  Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation
  Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), 28 November - 9 December 2022, New Orleans, USA
  
• Brandt, Jasmin; Bengs, Viktor; Haddenhorst, Björn; Hüllermeier, Eyke (2022)
  Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget
  Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), 28 November - 9 December 2022, New Orleans, USA
  
• Rodemann, Julian; Kreiss, Dominik; Hüllermeier, Eyke; Augustin, Thomas (2022)
  Levelwise Data Disambiguation by Cautious Superset Classification
  15th International Conference on Scalable Uncertainty Management, 17-19 October 2022, Paris, France
  
• Haas, Stefan; Hüllermeier, Eyke (2022)
  A Prescriptive Machine Learning Approach for Assessing Goodwill in the Automotive Domain
  Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2022), 19-23 September, 2023, Grenoble, France
  
• Hüllermeier, Eyke; Destercke, Sébastien; Shaker, Mohammad Hossein (2022)
  Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison
  38th Conference on Uncertainty in Artificial Intelligence, 1-5 August 2022, Eindhoven, Netherlands
  
• Mortier, Thomas; Hüllermeier, Eyke; Dembczyński, Krzysztof; Waegeman, Willem (2022)
  Set-valued prediction in hierarchical classification with constrained representation complexity
  38th Conference on Uncertainty in Artificial Intelligence, 1-5 August 2022, Eindhoven, Netherlands
  
• Bengs, Viktor; Saha, Aadirupa; Hüllermeier, Eyke (2022)
  Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models
  39th International Conference on Machine Learning, July 17-23 2022, Baltimore, MD, USA
  
• Tornede, Alexander; Bengs, Viktor; Hüllermeier, Eyke (2022)
  Machine Learning for Online Algorithm Selection under Censored Feedback
  Thirty-Sixth AAAI Conference on Artificial Intelligence, February 22–March 1, 2022, Virtual
  
• Sharma, Arnab; Melnikov, Vitalik; Hüllermeier, Eyke; Wehrheim, Heike (2022)
  Property-Driven Testing of Black-Box Functions
  2022 IEEE/ACM 10th International Conference on Formal Methods in Software Engineering (FormaliSE), 22-23 May 2022, Pittsburgh, PA, USA
  
• Schneider, Stefanie; Springstein, Matthias; Rahnama, Javad; Kohle, Hubertus; Ewerth, Ralph; Hüllermeier, Eyke (2022)
  iART - Eine Suchmaschine zur Unterstützung von bildorientierten Forschungsprozessen
  DHd 2022 Kulturen des digitalen Gedächtnisses. 8. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum", 7. - 11. März 2022, Potsdam
  
• Gupta, Pritha; Ramaswamy, Arunselvan; Drees, Jan Peter; Hüllermeier, Eyke; Priesterjahn, Claudia; Jager, Tibor (2022)
  Automated Information Leakage Detection: A New Method Combining Machine Learning and Hypothesis Testing with an Application to Side-channel Detection in Cryptographic Protocols
  14th International Conference on Agents and Artificial Intelligence (ICAART 2022), February 3-5, Virtual
  
• Campagner, Andrea; Lienen, Julian; Hüllermeier, Eyke; Ciucci, Davide (2022)
  Scikit-Weak: A Python Library for Weakly Supervised Machine Learning
  International Joint Conference on Rough Sets, 11-14 November 2022, Suzhou, China
  
• Sharma, Arnab; Melnikov, Vitalik; Hüllermeier, Eyke; Wehrheim, Heike (2022)
  Property-driven testing of black-box functions
  10th International Conference on Formal Methods in Software Engineering (FormaliSE '22), May 18 - 22, 2022, Pittsburgh Pennsylvania
  
• Haddenhorst, Björn; Bengs, Viktor; Hüllermeier, Eyke (2021)
  Identification of the Generalized Condorcet Winner in Multi-dueling Bandits
  Advances in Neural Information Processing Systems, December 7 2021, Virtual
  
• Lienen, Julian; Hüllermeier, Eyke (2021)
  Credal Self-Supervised Learning
  35th Conference on Neural Information Processing Systems (NeurIPS 2021), December 7, 2021, Virtual
  
• Lienen, Julian; Nommensen, Nils; Ewerth, Ralph; Hüllermeier, Eyke (2021)
  Robust Regression for Monocular Depth Estimation
  Asian Conference on Machine Learning, November 17 - 19, 2021, Virtual
  
• Bresson, Roman; Cohen, Johanne; Hüllermeier, Eyke; Labreuche, Christophe; Sebag, Michèle (2021)
  On the Identifiability of Hierarchical Decision Models
  International Conference on Principles of Knowledge Representation and Reasoning, November 3-12, 2021, Virtual
  
• Feldhans, Robert; Wilke, Adrian; Heindorf, Stefan; Shaker, Mohammad Hossein; Hammer, Barbara; Ngonga Ngomo, Axel-Cyrille; Hüllermeier, Eyke (2021)
  Drift Detection in Text Data with Document Embeddings
  Intelligent Data Engineering and Automated Learning – IDEAL 2021, November 25-27, 2021, Manchester, United Kingdom
  
• Drees, Jan Peter; Gupta, Pritha; Hüllermeier, Eyke; Jager, Tibor; Konze, Alexander; Priesterjahn, Claudia; Ramaswamy, Arunselvan; Somorovsky, Juraj (2021)
  Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!
  CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, 15. November 2021, Virtual Event, Republic of Korea
  
• Damke, Clemens; Hüllermeier, Eyke (2021)
  Ranking Structured Objects with Graph Neural Networks
  24th International Conference on Discovery Science (DS 2021), October 11–13, 2021, Halifax, NS, Canada, Virtual
  
• Springstein, Matthias; Schneider, Stefanie; Rahnama, Javad; Hüllermeier, Eyke; Kohle, Hubertus; Ewerth, Ralph (2021)
  iART: A Search Engine for Art-Historical Images to Support Research in the Humanities
  29th ACM International Conference on Multimedia, October 20 - 24, 2021, Virtual
  
• Rapp, Michael; Mencía, Eneldo Loza; Fürnkranz, Johannes; Hüllermeier, Eyke (2021)
  Gradient-Based Label Binning in Multi-label Classification
  Machine Learning and Knowledge Discovery in Databases, September 13–17, 2021, Bilbao, Spain
  
• Kolpaczki, Patrick; Bengs, Viktor; Hüllermeier, Eyke (2021)
  Identifying Top-k Players in Cooperative Games via Shapley Bandits
  LWDA’21: Lernen, Wissen, Daten, Analysen, 1. - 3. September, 2021, Munich, Germany
  
• Hüllermeier, Eyke; Mohr, Felix; Tornede, Alexander; Wever, Marcel (2021)
  Automated Machine Learning, Bounded Rationality, and Rational Metareasoning
  ECMLPKDD Workshop on Automating Data Science (ADS2021), 17 September 2021, Virtual
  
• Haddenhorst, Björn; Bengs, Viktor; Brandt, Jasmin; Hüllermeier, Eyke (2021)
  Testification of Condorcet Winners in dueling bandits
  Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, July 27-30, 2021, Virtual
  
• Tornede, Tanja; Tornede, Alexander; Wever, Marcel; Hüllermeier, Eyke (2021)
  Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance
  GECCO '21, Proceedings of the Genetic and Evolutionary Computation Conference Companion, 10 - 14 July, 2021, Lille, France
  
• Lienen, Julian; Hüllermeier, Eyke; Ewerth, Ralph; Nommensen, Nils (2021)
  Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 20-25 June 2021, Nashville, TN, USA
  
• Peeters, Sven; Melnikov, Vitalik; Hüllermeier, Eyke (2021)
  Performance Prediction for Hardware-Software Configurations: A Case Study for Video Games
  19th International Symposium on Intelligent Data Analysis, April 26–28, 2021, Porto, Portugal
  
• Ahmadi Fahandar, Mohsen; Hüllermeier, Eyke (2021)
  Analogical Embedding for Analogy-Based Learning to Rank
  Advances in Intelligent Data Analysis XIX. IDA 2021, April 26-28, 2021, Porto, Portugal
  
• Mohr, Felix; Bengs, Viktor; Hüllermeier, Eyke (2021)
  Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model
  AAAI Conference on Artificial Intelligence, February 2–9, 2021, Virtual
  
• Lienen, Julian; Hüllermeier, Eyke (2021)
  From Label Smoothing to Label Relaxation
  Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), February 2–9, 2021, Virtual
  
• Schneider, Stefanie; Springstein, Matthias; Rahnama, Javad; Hüllermeier, Eyke; Ewerth, Ralph; Kohle, Hubertus (2021)
  The Dissimilar in the Similar. An Attribute-guided Approach to the Subject-specific Classification of Art-historical Objects
  INFORMATIK 2020 - Back to the Future, 28 September - 2 October 2020, Virtual
  
• Tornede, Alexander; Wever, Marcel; Hüllermeier, Eyke (2020)
  Towards Meta-Algorithm Selection
  4th Workshop on Meta-Learning at NeurIPS, 11 December 2020, Virtual
  
• Damke, Clemens; Melnikov, Vitalik; Hüllermeier, Eyke (2020)
  A Novel Higher-order Weisfeiler-Lehman Graph Convolution
  12th Asian Conference on Machine Learning (ACML 2020), 18-20 November 2020, Bangkok, Thailand
  
• Tornede, Alexander; Wever, Marcel; Werner, Stefan; Mohr, Felix; Hüllermeier, Eyke (2020)
  Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
  12th Asian Conference on Machine Learning (ACML 2020), 18-20 November 2020, Bangkok, Thailand
  
• Heid, Stefan; Ramaswamy, Arunselvan; Hüllermeier, Eyke (2020)
  Constrained Multi-Agent Optimization with Unbounded Information Delay
  30. Workshop Computational Intelligence, 26. – 27. November 2020, Berlin, Germany
  
• Dari, Simone; Hüllermeier, Eyke (2020)
  Reliable Driver Gaze Classification based on Conformal Prediction
  30. Workshop Computational Intelligence, 26. – 27. November 2020, Berlin, Germany
  
• Nguyen, Vu-Linh; Hüllermeier, Eyke; Rapp, Michael; Loza Mencia, Eneldo; Fürnkranz, Johannes (2020)
  On Aggregation in Ensembles of Multilabel Classifiers
  23rd International Conference on Discovery Science, 19-21 October 2020, Virtual
  
• Tornede, Tanja; Tornede, Alexander; Wever, Marcel; Mohr, Felix; Hüllermeier, Eyke (2020)
  AutoML for Predictive Maintenance: One Tool to RUL Them All
  Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, September 14-18, 2020, Ghent, Belgium
  
• Hanselle, Jonas; Tornede, Alexander; Wever, Marcel; Hüllermeier, Eyke (2020)
  Hybrid Ranking and Regression for Algorithm Selection
  KI 2020: Advances in Artificial Intelligence. 43rd German Conference on AI, September 21–25, 2020, Bamberg, Germany
  
• Hüllermeier, Eyke (2020)
  Towards Analogy-Based Explanations in Machine Learning
  Modeling Decisions for Artificial Intelligence, September 2–4, 2020, Sant Cugat, Spain
  
• Hüllermeier, Eyke; Fürnkranz, Johannes; Loza Mencia, Eneldo; Nguyen, Vu-Linh; Rapp, Michael (2020)
  Rule-Based Multi-label Classification: Challenges and Opportunities
  4th International Joint Conference on Rules and Reasoning, 29 June - 1 July 2020, Virtual
  
• Dari, Simone; Kadrileev, Nikolay; Hüllermeier, Eyke (2020)
  A Neural Network-Based Driver Gaze Classification System with Vehicle Signals
  2020 International Joint Conference on Neural Networks (IJCNN), 19-24 July 2020, Glasgow, UK
  
• Bengs, Viktor; Hüllermeier, Eyke (2020)
  Preselection Bandits
  37th International Conference on Machine Learning, July 12-18 2020, Virtual
  
• Rahnama, Javad; Hüllermeier, Eyke (2020)
  Learning Tversky Similarity
  International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, 15-19 June 2020, Lisbon, Portugal
  
• Campagner, Andrea; Ciucci, Davide; Hüllermeier, Eyke (2020)
  Feature Reduction in Superset Learning Using Rough Sets and Evidence Theory
  International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, 15-19 June 2020, Lisbon, Portugal
  
• Shaker, Mohammad Hossein; Hüllermeier, Eyke (2020)
  Aleatoric and Epistemic Uncertainty with Random Forests
  International Symposium on Intelligent Data Analysis, April 27-29 2020, Bodenseeforum, Lake Constance, Germany
  
• Nguyen, Vu-Linh; Hüllermeier, Eyke (2020)
  Reliable Multilabel Classification: Prediction with Partial Abstention
  34th AAAI Conference on Artificial Intelligence, 7-12 Feburary 2020, New York, USA
  
• Hüllermeier, Eyke; Fürnkranz, Johannes; Loza Mencia, Eneldo (2020)
  Conformal Rule-Based Multi-label Classification
  KI 2020: Advances in Artificial Intelligence. 43rd German Conference on AI, September 21–25, 2020, Bamberg, Germany
  
• Pfannschmidt, Karlson; Hüllermeier, Eyke (2020)
  Learning Choice Functions via Pareto-Embeddings
  43rd German Conference on AI, 21-25 September, 2020, Bamberg, Germany
  
• Bresson, Roman; Cohen, Johanne; Hüllermeier, Eyke; Labreuche, Christophe; Sebag, Michèle (2020)
  Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals
  Twenty-Ninth International Joint Conference on Artificial Intelligence, January 7-15, 2021, Yokohama, Japan (Virtual)
  
• Tornede, Alexander; Wever, Marcel; Hüllermeier, Eyke (2019)
  Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking. , KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–146.
  29. Workshop Computational Intelligence, 28. - 29. November 2019, Dortmund, Germany
  
• Wever, Marcel Dominik; Mohr, Felix; Tornede, Alexander; Hüllermeier, Eyke (2019)
  Automating Multi-Label Classification Extending ML-Plan
  6th ICML Workshop on Automated Machine Learning (AutoML 2019), June 14th 2019, Long Beach, California, USA
  
• Wever, Marcel; Mohr, Felix; Hüllermeier, Eyke; Hetzer, Alexander (2019)
  Towards Automated Machine Learning for Multi-Label Classification
  ECDA 2019: European Conference on Data Analysis, 18 - 20 March 2019, Bayreuth, Germany
  
• Hetzer, Alexander; Wever, Marcel; Mohr, Felix; Hüllermeier, Eyke (2019)
  Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking
  ECDA 2019: European Conference on Data Analysis, 18 - 20 March 2019, Bayreuth, Germany
  
• Melnikov, Vitalik; Hüllermeier, Eyke (2019)
  Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA
  11th Asian Conference on Machine Learning (ACML 2019), November 17 - 19, 2019, Nagoya, Japan
  
• Mohr, Felix; Hüllermeier, Eyke; Wever, Marcel (2018)
  ML-Plan for Unlimited-Length Machine Learning Pipelines
  ICML 2018 AutoML Workshop, 2018-07-10 – 2018-07-15, Stockholm, Sweden
  
• Mohr, Felix; Lettmann, Theodor; Hüllermeier, Eyke; Wever, Marcel Dominik (2018)
  Programmatic Task Network Planning
  28th International Conference on Automated Planning and Scheduling, 2018-06-24 – 2018-06-29, Delft, Netherlands
  
• Seemann, Nina; Geierhos, Michaela; Merten, Marie-Luis; Tophinke, Doris; Wever, Marcel Dominik; Hüllermeier, Eyke (2018)
  Supporting the Cognitive Process in Annotation Tasks
  40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, 2018-03-07 – 2018-03-09, Stuttgart, Germany
  
• Mohr, Felix; Wever, Marcel; Hüllermeier, Eyke; Faez, Amin (2018)
  (WIP) Towards the Automated Composition of Machine Learning Services
  2018 IEEE International Conference on Services Computing (SCC), 2-7 July 2018, San Francisco, CA, USA
  
• Wever, Marcel; Mohr, Felix; Hüllermeier, Eyke (2018)
  Ensembles of evolved nested dichotomies for classification
  GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference, July 15 - 19, 2018, Kyoto, Japan
  
• Mohr, Felix; Wever, Marcel; Hüllermeier, Eyke (2018)
  On-the-Fly Service Construction with Prototypes
  2018 IEEE International Conference on Services Computing (SCC), 2-7 July 2018, San Francisco, CA, USA
  
• Nguyen, Vu-Linh; Destercke, Sébastien; Masson, Marie-Hélène; Hüllermeier, Eyke (2018)
  Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty
  Twenty-Seventh International Joint Conference on Artificial Intelligence, 13-19 July 2018, Stockholm, Sweden
  
• El Mesaoudi-Paul, Adil; Hüllermeier, Eyke; Busa-Fekete, Róbert (2018)
  Ranking Distributions based on Noisy Sorting
  35th International Conference on Machine Learning, 10-15 July 2018, Stockholm, Sweden
  
• Ahmadi Fahandar, Mohsen; Hüllermeier, Eyke (2018)
  Learning to rank based on analogical reasoning
  32nd AAAI Conference on Artificial Intelligence, 2-7 February 2018, New Orleans, Louisianna, USA
  
• Seemann, Nina; Merten, Marie-Luis; Geierhos, Michaela; Tophinke, Doris; Hüllermeier, Eyke (2017)
  Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German
  Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, August, 2017, Vancouver, Canada
  
• Ahmadi Fahandar, Mohsen; Hüllermeier, Eyke; Couso, Inés (2017)
  Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
  34th International Conference on Machine Learning, $pub.event_dates, Sydney, Australia (full text available)
  
• Czech, Mike; Hüllermeier, Eyke; Jakobs, Marie-Christine; Wehrheim, Heike (2017)
  Predicting rankings of software verification tools
  3rd ACM SIGSOFT International Workshop on Software Analytics, 4 September 2017, Paderborn, Germany
  
• Ewerth, Ralph; Springstein, Matthias; Müller, Eric; Balz, Alexander; Gehlhaar, Jan; Naziyok, Tolga; Dembczyński, Krzysztof; Hüllermeier, Eyke (2017)
  Estimating relative depth in single images via rankboost
  2017 IEEE International Conference on Multimedia and Expo (ICME), 10-14 July 2017, Hong Kong
  
• Wever, Marcel Dominik; Mohr, Felix; Hüllermeier, Eyke (2017)
  Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization
  27th Workshop Computational Intelligence, 23. – 24. November 2017, Dortmund
  
• Jasinska, Kalina; Dembczynski, Krzysztof; Busa-Fekete, Róbert; Pfannschmidt, Karlson; Klerx, Timo; Hüllermeier, Eyke (2016)
  Extreme F-measure maximization using sparse probability estimates
  ICML'16: 33rd International Conference on International Conference on Machine Learning, June 19 - 24, 2016, New York, NY USA
  
• Schäfer, Dirk; Hüllermeier, Eyke (2016)
  Plackett-Luce Networks for Dyad Ranking
  LWDA 2016: Lernen, Wissen, Daten, Analysen 2016, September 12-14, 2016, Potsdam, Germany
  
• Schäfer, Dirk; Hüllermeier, Eyke (2015)
  Preference-based meta-learning using dyad ranking: recommending algorithms in cold-start situations
  MetaSel'15: International Conference on Meta-Learning and Algorithm Selection, 7 September 2015, Porto Portugal
  
• Szörényi, Baiÿzs; Busa-Fekete, Róbert; Paul, Adil; Hüllermeier, Eyke (2015)
  Online rank elicitation for Plackett-Luce: a dueling bandits approach
  NIPS'15: 28th International Conference on Neural Information Processing Systems, December 7 - 12, 2015, Montreal Canada
  
• Szörényi, Baiÿzs; Busa-Fekete, Róbert; Paul, Adil; Hüllermeier, Eyke (2015)
  Online F-measure optimization
  NIPS'15: 28th International Conference on Neural Information Processing Systems, December 7 - 12, 2015, Montreal Canada
  
• Paul, Adil; Hüllermeier, Eyke (2015)
  A CBR Approach to the Angry Birds Game
  Twenty-Third International Conference on Case-Based Reasoning (ICCBR 2015), September 28-30, 2015, Frankfurt, Germany
  
• Szörényi, Balázs; Busa-Fekete, Róbert; Weng, Paul; Hüllermeier, Eyke (2015)
  Qualitative Multi-Armed Bandits: A Quantile-Based Approach
  32nd International Conference on Machine Learning, July 6 - 11, 2015, Lille, France
  
• Busa-Fekete, Róbert; Szörényi, Balázs; Hüllermeier, Eyke (2014)
  PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences
  28th AAAI Conference on Artificial Intelligence (AAAI-14), Jul 2014, Quebec City, Canada
  
• Fallah Tehrani, Ali; Strickert, Marc; Hüllermeier, Eyke (2014)
  The Choquet kernel for monotone data
  22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 23-25 April 2014, Bruges (Belgium)