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

• Camberg, Simone; Hüllermeier, Eyke (2024)
  An Extensive Analysis of Different Approaches to Driver Gaze Classification
  In: IEEE Transactions on Intelligent Transportation Systems, Vol. 25, No. 11: pp. 16435-16448
  
• Heid, Stefan; Wever, Marcel Dominik; Hüllermeier, Eyke (2024)
  Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction
  In: Journal of Data Mining & Digital Humanities (full text available)
  
• Haas, Stefan; Hegestweiler, Konstantin; Rapp, Michael; Muschalik, Maximilian; Hüllermeier, Eyke (2024)
  Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments
  In: Frontiers in Artificial Intelligence, Vol. 7 (full text available)
  
• Heid, Stefan; Wever, Marcel; Hüllermeier, Eyke (2024)
  Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction
  In: Journal of Data Mining & Digital Humanities (full text available)
  
• Haas, Stefan; Hüllermeier, Eyke (2024)
  Conformalized prescriptive machine learning for uncertainty-aware automated decision making: the case of goodwill requests
  In: International Journal of Data Science and Analytics (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Rapp, Michael; Fürnkranz, Johannes; Hüllermeier, Eyke (2023)
  On the efficient implementation of classification rule learning
  In: Advances in Data Analysis and Classification, Vol. 18: pp. 851-892 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Bengs, Viktor; Hüllermeier, Eyke (2022)
  Multi-armed bandits with censored consumption of resources
  In: Machine Learning, Vol. 112, No. 2: pp. 217-240 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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
  
• 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
  In: Journal of Open Source Software, Vol. 5, No. 54: pp. 2435 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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
  
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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
  
• 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
  
• 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 (full text available)
  
• 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
  
• 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
  
• 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
  
• 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 (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

• Javanmardi, Alireza; Stutz, David; Hüllermeier, Eyke (2024)
  Conformalized Credal Set Predictors
  The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), 10. -15. December 2024, Vancouver, BC, Canada (full text available)
  
• Heid, Stefan; Kornowicz, Jaroslaw; Hüllermeier, Eyke; Thommes, Kirsten (2024)
  Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems
  34. Workshop Computational Intelligence, 21.-22. November 2024, Berlin, Germany (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Muschalik, Maximilian; Fumagalli, Fabian; Hammer, Barbara; Hüllermeier, Eyke (2024)
  Explaining Change in Models and Data with Global Feature Importance and Effects
  TempXAI: Explainable AI for Time Series and Data Streams Tutorial-Workshop, 9. - 13. September 2024, Vilnius, Lithuania (full text available)
  
• Brandt, Jasmin; Wever, Marcel; Bengs, Viktor; Hüllermeier, Eyke (2024)
  Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO
  Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24), 3. - 9. August 2024, Jeju, South Korea
  
• Kaufmann, Timo; Blüml, Jannis; Wüst, Antonia; Delfosse, Quentin; Kersting, Kristian; Hüllermeier, Eyke (2024)
  OCALM: Object-Centric Assessment with Language Models
  Reinforcement Learning Conference (RLC 2024) Workshop on Reinforcement Learning Beyond Rewards (RLBRew), 9. August 2024, Amherst, MA, USA
  
• Javanmardi, Alireza; Aimiyekagbon, Osarenren Kennedy; Bender, Amelie; Kimotho, James Kuria; Sextro, Walter; Hüllermeier, Eyke (2024)
  Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions
  PHM Society European Conference, 3. - 5. July 2024, Prague, Czech Republic (full text available)
  
• 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; Hammer, Barbara (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)
  
• Sale, Yusuf; 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)
  
• Kolpaczki, Patrick; Haselbeck, Georg; Hüllermeier, Eyke (2024)
  How Much Can Stratification Improve the Approximation of Shapley Values?
  Explainable Artificial Intelligence, 17. –19. July 2024, Valletta, Malta
  
• 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 (full text available)
  
• Lienen, Julian; Hüllermeier, Eyke (2024)
  Mitigating Label Noise through Data Ambiguation
  AAAI Conference on Artificial Intelligence 2024, 20-27 February 2024, Vancouver, Canada (full text available)
  
• 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 (full text available)
  
• Kaufmann, Timo; Bengs, Viktor; Hüllermeier, Eyke (2024)
  Reinforcement Learning from Human Feedback for Cyber-Physical Systems: On the Potential of Self-Supervised Pretraining
  International Conference on Machine Learning For Cyber-Physical Systems (ML4CPS 2023), 29. - 31. March 2023, Hamburg, Germany (full text available)
  
• Muschalik, Maximilian; Baniecki, Hubert; Fumagalli, Fabian; Kolpaczki, Patrick; Hammer, Barbara; Hüllermeier, Eyke (2024)
  shapiq: Shapley Interactions for Machine Learning
  The Thirty-eight Conference on Neural Information Processing Systems (NeurIPS 2024), 10. - 15. December 2024, Vancouver, BC, Canada (full text available)
  
• 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; Hammer, Barbara (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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Kaufmann, Timo; Ball, Sarah; Beck, Jakob; Hüllermeier, Eyke; Kreuter, Frauke (2023)
  On the challenges and practices of reinforcement learning from real human feedback
  First ECMLPKDD Workshop on Hybrid Human-Machine Learning and Decision Making, 22. September 2023, Turin, Italy (full text available) [forthcoming]
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 2022), 28 November - 9 December 2022, New Orleans, USA (full text available)
  
• 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 2022), 28 November - 9 December 2022, New Orleans, USA (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Lienen, Julian; Hüllermeier, Eyke (2021)
  Credal Self-Supervised Learning
  35th Conference on Neural Information Processing Systems (NeurIPS 2021), December 7, 2021, Virtual (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Bernijazov, Ruslan; Dicks, Alexander; Dumitrescu, Roman; Foullois, Marc; Hanselle, Jonas; Hüllermeier, Eyke; Karakaya, Gökce; Ködding, Patrick; Lohweg, Volker; Malatyali, Manuel; Meyer Auf der Heide, Friedhelm; Panzner, Melina; Soltenborn, Christian (2021)
  A Meta-Review on Artificial Intelligence in Product Creation
  AI and Product Design Workshop, 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 19. August 2021, Montreal, Quebec, Canada (full text available)
  
• 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 (full text available)
  
• 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
  
• Bresson, Roman; Cohen, Johanne; Hüllermeier, Eyke; Labreuche, Christophe; Sebag, Michèle (2021)
  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)
  
• 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 (full text available)
  
• Tornede, Alexander; Wever, Marcel; Hüllermeier, Eyke (2020)
  Towards Meta-Algorithm Selection
  4th Workshop on Meta-Learning at NeurIPS, 11 December 2020, Virtual (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Dari, Simone; Hüllermeier, Eyke (2020)
  Reliable Driver Gaze Classification based on Conformal Prediction
  30. Workshop Computational Intelligence, 26. – 27. November 2020, Berlin, Germany (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Hüllermeier, Eyke (2020)
  Towards Analogy-Based Explanations in Machine Learning
  Modeling Decisions for Artificial Intelligence, September 2–4, 2020, Sant Cugat, Spain (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Pfannschmidt, Karlson; Hüllermeier, Eyke (2020)
  Learning Choice Functions via Pareto-Embeddings
  43rd German Conference on AI, 21-25 September, 2020, Bamberg, Germany (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• 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 (full text available)
  
• Mohr, Felix; Hüllermeier, Eyke; Weve