Chair of Artificial Intelligence and Machine Learning
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  • 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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