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2025

Jonas Hanselle, Stefan Heid, Johannes Fürnkranz, Eyke Hüllermeier (2025)
Probabilistic scoring lists for interpretable machine learning(bib)(pdf)
In: Machine Learning, Vol. 114, No. 3
Mohamed Karim Belaid, Maximilian Rabus, Eyke Hüllermeier (2025)
Pairwise Difference Learning for Classification(bib)(preprint)
27th International Conference, DS 2024, October 14–16, 2024, Pisa, Italy
Elena Terzieva, Maximilian Muschalik, Paul Hofman, Eyke Hüllermeier (2025)
Identifying Trends in Feature Attributions During Training of Neural Networks(bib)(pres)
Uncertainty meets Explainability Workshop, ECML-PKDD 2023, September 18, 2023, Turin, Italy
Nastaran Saberi, Mohammad Hossein Shaker, Claude R. Duguay, K Andrea Scott, Eyke Hüllermeier (2025)
Uncertainty Estimation of Lake Ice Cover Maps From a Random Forest Classifier Using MODIS TOA Reflectance Data(bib)(pdf)
In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 18: pp. 5919-5927

2024

Maximilian Muschalik, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara Hammer, Eyke Hüllermeier (2024)
shapiq: Shapley Interactions for Machine Learning(bib)(pdf)(pres)
The Thirty-eight Conference on Neural Information Processing Systems (NeurIPS 2024), 10. - 15. December 2024, Vancouver, BC, Canada
Alireza Javanmardi, David Stutz, Eyke Hüllermeier (2024)
Conformalized Credal Set Predictors(bib)(pdf)(pres)
The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), 10. -15. December 2024, Vancouver, BC, Canada
Stefan Heid, Jaroslaw Kornowicz, Eyke Hüllermeier, Kirsten Thommes (2024)
Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems(bib)(pdf)
34. Workshop Computational Intelligence, 21.-22. November 2024, Berlin, Germany
Dimitrios Iliadis, Marcel Wever, Bernard De Baets, Willem Waegeman (2024)
Hyperparameter optimization of two-branch neural networks in multi-target prediction(bib)(preprint)
In: Applied Soft Computing, Vol. 165: pp. 111957
Simone Camberg, Eyke Hüllermeier (2024)
An Extensive Analysis of Different Approaches to Driver Gaze Classification(bib)
In: IEEE Transactions on Intelligent Transportation Systems, Vol. 25, No. 11: pp. 16435-16448
Stefan Haas, Konstantin Hegestweiler, Michael Rapp, Maximilian Muschalik, Eyke Hüllermeier (2024)
Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments(bib)(pdf)
In: Frontiers in Artificial Intelligence, Vol. 7
Stefan Heid, Marcel Wever, Eyke Hüllermeier (2024)
Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction(bib)(pdf)
In: Journal of Data Mining & Digital Humanities
Stefan Heid, Marcel Wever, Eyke Hüllermeier (2024)
Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction(bib)(pdf)
In: Journal of Data Mining & Digital Humanities
Clemens Damke, Eyke Hüllermeier (2024)
CUQ-GNN: Committee-Based Graph Uncertainty Quantification Using Posterior Networks(bib)(preprint)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 9. - 13. September 2024, Vilnius, Lithuania
Eyke Hüllermeier, Roman Słowiński (2024)
Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies—part II(bib)(pdf)
In: 4OR - A Quarterly Journal of Operations Research, Vol. 22, No. 3: pp. 313-349
Amihossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei (2024)
Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning(bib)(preprint)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 9. - 13. September 2024, Vilnius, Lithuania
Raphael Fischer, Marcel Wever, Sebastian Buschjäger, Thomas Liebig (2024)
MetaQuRe: Meta-learning from Model Quality and Resource Consumption(bib)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 9. - 13. September 2024, Vilnius, Lithuania
Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier (2024)
Explaining Change in Models and Data with Global Feature Importance and Effects(bib)(pdf)
TempXAI: Explainable AI for Time Series and Data Streams Tutorial-Workshop, 9. - 13. September 2024, Vilnius, Lithuania
Stefan Heid, Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier (2024)
Learning decision catalogues for situated decision making: The case of scoring systems(bib)(pdf)
In: International Journal of Approximate Reasoning, Vol. 171
Timo Kaufmann, Jannis Blüml, Antonia Wüst, Quentin Delfosse, Kristian Kersting, Eyke Hüllermeier (2024)
OCALM: Object-Centric Assessment with Language Models(bib)
Reinforcement Learning Conference (RLC 2024) Workshop on Reinforcement Learning Beyond Rewards (RLBRew), 9. August 2024, Amherst, MA, USA
Jasmin Brandt, Marcel Wever, Viktor Bengs, Eyke Hüllermeier (2024)
Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO(bib)
Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24), 3. - 9. August 2024, Jeju, South Korea
Timo Löhr, Michael Ingrisch, Eyke Hüllermeier (2024)
Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification(bib)
22nd International Conference of Artificial Intelligence in Medicine (AIME 2024), 9. - 12. July 2024, Salt Lake City, Utah, USA
Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier (2024)
Label-wise Aleatoric and Epistemic Uncertainty Quantification(bib)(pdf)
Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, 15. - 19. July 2024, Barcelona, Spain
Clemens Damke, Eyke Hüllermeier (2024)
Linear Opinion Pooling for Uncertainty Quantification on Graphs(bib)(pdf)
Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, 15. - 19. July 2024, Barcelona, Spain
Patrick Kolpaczki, Georg Haselbeck, Eyke Hüllermeier (2024)
How Much Can Stratification Improve the Approximation of Shapley Values?(bib)
Explainable Artificial Intelligence, 17. –19. July 2024, Valletta, Malta
Mira Juergens, Nis Meinert, Viktor Bengs, Eyke Hüllermeier, Willem Waegeman (2024)
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?(bib)(pdf)
41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke HÜllermeier, Barbara Hammer (2024)
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions(bib)(pdf)(pres)
41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl (2024)
Position: Why We Must Rethink Empirical Research in Machine Learning(bib)(pdf)
41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria
Yusuf Sale, Viktor Bengs, Michele Caprio, Eyke Hüllermeier (2024)
Second-Order Uncertainty Quantification: A Distance-Based Approach(bib)(pdf)
41st International Conference on Machine Learning (ICML 2024), 21. - 27. July 2024, Vienna, Austria
Alireza Javanmardi, Osarenren Kennedy Aimiyekagbon, Amelie Bender, James Kuria Kimotho, Walter Sextro, Eyke Hüllermeier (2024)
Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions(bib)(pdf)
PHM Society European Conference, 3. - 5. July 2024, Prague, Czech Republic
Timo Kaufmann, Viktor Bengs, Eyke Hüllermeier (2024)
Reinforcement Learning from Human Feedback for Cyber-Physical Systems: On the Potential of Self-Supervised Pretraining(bib)(pdf)(pres)
International Conference on Machine Learning For Cyber-Physical Systems (ML4CPS 2023), 29. - 31. March 2023, Hamburg, Germany
Stefan Haas, Eyke Hüllermeier (2024)
Conformalized prescriptive machine learning for uncertainty-aware automated decision making: the case of goodwill requests(bib)(pdf)
In: International Journal of Data Science and Analytics
Eyke Hüllermeier, Roman Słowiński (2024)
Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies–part I(bib)(pdf)
In: 4OR, Vol. 22, No. 2: pp. 179-209
Amirhossein Vahidi, Simon Schosser, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei (2024)
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization(bib)(pdf)
12th International Conference on Learning Representations (ICLR 2024), 7. - 11. May 2024, Vienna, Austria
Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier (2024)
Identifying Copeland Winners in Dueling Bandits with Indifferences(bib)(pdf)(pres)
27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2. - 4. May 2024, Valencia, Spain
Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier (2024)
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification(bib)(pdf)(pres)
27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2. - 4. May 2024, Valencia, Spain
Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven (2024)
Continual Learning: Applications and the Road Forward(bib)(pdf)(pres)
In: Transactions on Machine Learning Research
Patrick Kolpaczki, Viktor Bengs, Maximilian Muschalik, Eyke Hüllermeier (2024)
Approximating the Shapley Value without Marginal Contributions(bib)(preprint)(pres)
AAAI Conference on Artificial Intelligence 2024, 20-27 February 2024, Vancouver, Canada
Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier (2024)
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles(bib)(preprint)(pres)
AAAI Conference on Artificial Intelligence 2024, 20-27 February 2024, Vancouver, Canada
Julian Lienen, Eyke Hüllermeier (2024)
Mitigating Label Noise through Data Ambiguation(bib)(pres)
AAAI Conference on Artificial Intelligence 2024, 20-27 February 2024, Vancouver, Canada

2023

Petar Bevanda, Max Beier, Armin Lederer, Stefan Sosnowski, Eyke Hüllermeier, Sandra Hirche (2023)
Koopman Kernel Regression(bib)(pdf)(suppl)
37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), 10. - 16. December 2023, New Orleans, Louisiana, USA
Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer (2023)
SHAP-IQ: Unified Approximation of any-order Shapley Interactions(bib)(pdf)(suppl)
37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), 10. - 16. December 2023, New Orleans, Louisiana, USA
Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier (2023)
Probabilistic Scoring Lists for Interpretable Machine Learning(bib)(preprint)
26th International Conference on Discovery Science (DS 2023), October 9-11, 2023, Porto, Portugal
Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer (2023)
On Feature Removal for Explainability in Dynamic Environments(bib)(pdf)
ESANN 2023 - European Symposium on Artificial Neural Networks, 4-6 October 2023, Bruges, Belgium
Jonas Hanselle, Jaroslaw Kornowicz, Stefan Heid, Kirsten Thommes, Eyke Hüllermeier (2023)
Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain(bib)(pdf)
Lernen, Wissen, Daten, Analysen (LWDA), 9-11 October 2023, Marburg, Germany
Jasmin Brandt, Elias Schede, Shivam Sharma, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney (2023)
Contextual Preselection Methods in Pool-based Realtime Algorithm Configuration(bib)(pdf)
Lernen, Wissen, Daten, Analysen (LWDA), 9-11 October 2023, Marburg, Germany
Timo Kaufmann, Sarah Ball, Jakob Beck, Eyke Hüllermeier, Frauke Kreuter (2023)
On the challenges and practices of reinforcement learning from real human feedback(bib)(pres)
First ECMLPKDD Workshop on Hybrid Human-Machine Learning and Decision Making, 22. September 2023, Turin, Italy
Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer (2023)
Incremental permutation feature importance (iPFI): towards online explanations on data streams(bib)(pdf)
In: Machine Learning, Vol. 112, No. 12: pp. 4863-4903
Stefan Haas, Eyke Hüllermeier (2023)
Rectifying Bias in Ordinal Observational Data Using Unimodal Label Smoothing(bib)
Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 18-22 September, 2023, Torino, Italy
Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier (2023)
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams(bib)(preprint)
Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 18-22 September, 2023, Torino, Italy
Julian Lienen, Caglar Demir, Eyke Hüllermeier (2023)
Conformal Credal Self-Supervised Learning(bib)(pdf)
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023), September 13-15, 2023, Limassol, Cyprus
Alireza Javanmardi, Yusuf Sale, Paul Hofman, Eyke Hüllermeier (2023)
Conformal Prediction with Partially Labeled Data(bib)(pdf)
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023), September 13-15, 2023, Limassol, Cyprus
Pritha Gupta, Jan Peter Drees, Eyke Hüllermeier (2023)
Automated Side-Channel Attacks using Black-Box Neural Architecture Search(bib)(preprint)
18th International Conference on Availability, Reliability and Security, 29 August - 1 September 2023, Benevento, Italy
Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney (2023)
A Survey of Methods for Automated Algorithm Configuration (Extended Abstract)(bib)
Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI 2023), 19-25 August 2023, Macao, S.A.R
Michele Caprio, Yusuf Sale, Eyke Hüllermeier, Insup Lee (2023)
A Novel Bayes’ Theorem for Upper Probabilities(bib)(preprint)
Epi UAI 2023 - First International Workshop on Epistemic Uncertainty in Artificial Intelligence, August 4, 2023, Pittsburgh, PA, USA
Yusuf Sale, Michele Caprio, Eyke Hüllermeier (2023)
Is the volume of a credal set a good measure for epistemic uncertainty?(bib)(pdf)(suppl)
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), 1-3 August, 2023, Pittsburgh, PA, USA
Lisa Wimmer, Yusuf Sale, Paul Hofman, Bernd Bischl, Eyke Hüllermeier (2023)
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?(bib)(pdf)(pres)(suppl)
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), 1-3 August, 2023, Pittsburgh, PA, USA
Michael Rapp, Johannes Fürnkranz, Eyke Hüllermeier (2023)
On the efficient implementation of classification rule learning(bib)(pdf)
In: Advances in Data Analysis and Classification, Vol. 18: pp. 851-892
Alireza Javanmardi, Eyke Hüllermeier (2023)
Conformal Prediction Intervals for Remaining Useful Lifetime Estimation(bib)(pdf)
In: International Journal of Prognostics and Health Management, Vol. 14, No. 2
Alessandro Giovagnoli, Volker Tresp, Yunpu Ma, Matthias Schubert (2023)
QNEAT: Natural Evolution of Variational Quantum Circuit Architecture(bib)
GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation, July 15 - 19, 2023, Lisbon Portugal
Marcel Wever, Miran Özdogan, Eyke Hüllermeier (2023)
Cooperative Co-Evolution for Ensembles of Nested Dichotomies for Multi-Class Classification(bib)
Genetic and Evolutionary Computation Conference (GECCO '23), July 15-19, 2023, Lisbon, Portugal
Viktor Bengs, Eyke Hüllermeier, Willem Waegeman (2023)
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification(bib)(pdf)
40th International Conference on Machine Learning (ICML 2023), 23-29 July, 2023, Hawaii, USA
Mohamed Karim Belaid, Richard Bornemann, Maximilian Rabus, Ralf Krestel, Eyke Hüllermeier (2023)
Compare-xAI: Toward Unifying Functional Testing Methods for Post-hoc XAI Algorithms into a Multi-dimensional Benchmark(bib)(preprint)
World Conference on Explainable Artificial Intelligence (xAI 2023), 26-28 July 2023, Lisboa, Portugal
Maximilian Muschalik, Fabian Fumagalli, Rohit Jagtani, Barbara Hammer, Eyke Hüllermeier (2023)
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios(bib)
World Conference on Explainable Artificial Intelligence (xAI 2023), 26-28 July 2023, Lisboa, Portugal
Yao Zhang, Yunpu Ma, Thomas Seidl, Volker Tresp (2023)
Adaptive Multi-Resolution Attention with Linear Complexity(bib)
2023 International Joint Conference on Neural Networks (IJCNN), 18-23 June 2023, Gold Coast, Australia
Tanja Tornede, Alexander Tornede, Jonas Hanselle, Felix Mohr, Marcel Wever, Eyke Hüllermeier (2023)
Towards Green Automated Machine Learning: Status Quo and Future Directions(bib)(pdf)
In: Journal of Artificial Intelligence Research, Vol. 77: pp. 427-457
Anna-Katharina Wickert, Clemens Damke, Lars Baumgärtner, Eyke Hüllermeier, Mira Mezini (2023)
UnGoML: Automated Classification of unsafe Usages in Go(bib)(preprint)
20th International Conference on Mining Software Repositories (MSR), 15-16 May, 2023, Melbourne, Australia
Duc Anh Nguyen, Ron Levie, Julian Lienen, Eyke Hüllermeier, Gitta Kutyniok (2023)
Memorization-Dilation: Modeling Neural Collapse Under Noise(bib)(pdf)(suppl)
The Eleventh International Conference on Learning Representations, 1-5 May, 2023, Kigali, Rwanda
Michael Dellnitz, Eyke Hüllermeier, Marvin Lücke, Sina Ober-Blöbaum, Christian Offen, Sebastian Peitz, Karlson Pfannschmidt (2023)
Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning(bib)(preprint)
In: SIAM Journal on Scientific Computing, Vol. 45, No. 2: pp. A579-A595
Tanja Tornede, Alexander Tornede, Lukas Fehring, Lukas Gehring, Helena Graf, Jonas Hanselle, Felix Mohr, Marcel Wever (2023)
PyExperimenter: Easily distribute experiments and track results(bib)(pdf)
In: Journal of Open Source Software, Vol. 8, No. 84: pp. 5149
David Schubert, Pritha Gupta, Marcel Wever (2023)
Meta-learning for Automated Selection of Anomaly Detectors for Semi-supervised Datasets(bib)(preprint)
Advances in Intelligent Data Analysis XXI, 12-14 April 2023, Louvain-la-Neuve, Belgium
Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman (2023)
On the Calibration of Probabilistic Classifier Sets(bib)(pdf)
26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), 25-27 April, 2023, Valencia, Spain
Alexander Tornede, Lukas Gehring, Tanja Tornede, Marcel Wever, Eyke Hüllermeier (2023)
Algorithm selection on a meta level(bib)(pdf)
In: Machine Learning, Vol. 112, No. 4: pp. 1253-1286
Felix Mohr, Marcel Wever (2023)
Naive automated machine learning(bib)(pdf)
In: Machine Learning, Vol. 112, No. 4: pp. 1131-1170
Jasmin Brandt, Elias Schede, Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney (2023)
AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration(bib)(preprint)
AAAI Conference on Artificial Intelligence, February, 2023, Washington, DC, USA
Arnab Sharma, Vitalik Melnikov, Eyke Hüllermeier, Heike Wehrheim (2023)
Property-Driven Black-Box Testing of Numeric Functions(bib)(pdf)
Software Engineering 2023, 20-24 February 2023, Paderborn, Germany

2022

Lukas Fehring, Jonas Hanselle, Alexander Tornede (2022)
HARRIS: Hybrid Ranking and Regression Forests for Algorithm Selection(bib)(pdf)
Sixth Workshop on Meta-Learning (MetaLearn 2022) at the Conference on Neural Information Processing Systems (NeurIPS 2022), 2. December 2022, New Orleans, Louisiana, U.S.A.
Jasmin Brandt, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier (2022)
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget(bib)(pdf)(suppl)
Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), 28 November - 9 December 2022, New Orleans, USA
Viktor Bengs, Eyke Hüllermeier, Willem Waegeman (2022)
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation(bib)(pdf)(suppl)
Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), 28 November - 9 December 2022, New Orleans, USA
Viktor Bengs, Eyke Hüllermeier (2022)
Multi-armed bandits with censored consumption of resources(bib)(pdf)
In: Machine Learning, Vol. 112, No. 2: pp. 217-240
Andrea Campagner, Julian Lienen, Eyke Hüllermeier, Davide Ciucci (2022)
Scikit-Weak: A Python Library for Weakly Supervised Machine Learning(bib)
International Joint Conference on Rough Sets, 11-14 November 2022, Suzhou, China
Julian Rodemann, Dominik Kreiss, Eyke Hüllermeier, Thomas Augustin (2022)
Levelwise Data Disambiguation by Cautious Superset Classification(bib)
15th International Conference on Scalable Uncertainty Management, 17-19 October 2022, Paris, France
Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney (2022)
A Survey of Methods for Automated Algorithm Configuration(bib)(pdf)
In: Journal of Artificial Intelligence Research, Vol. 75: pp. 425-487
Stefan Haas, Eyke Hüllermeier (2022)
A Prescriptive Machine Learning Approach for Assessing Goodwill in the Automotive Domain(bib)
Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2022), 19-23 September, 2023, Grenoble, France
Eyke Hüllermeier, Sébastien Destercke, Mohammad Hossein Shaker (2022)
Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison(bib)(pdf)(suppl)
38th Conference on Uncertainty in Artificial Intelligence, 1-5 August 2022, Eindhoven, Netherlands
Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczyński, Willem Waegeman (2022)
Set-valued prediction in hierarchical classification with constrained representation complexity(bib)(pdf)(suppl)
38th Conference on Uncertainty in Artificial Intelligence, 1-5 August 2022, Eindhoven, Netherlands
Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier (2022)
Agnostic Explanation of Model Change based on Feature Importance(bib)(pdf)
In: KI - Künstliche Intelligenz, Vol. 36, No. 3-4: pp. 211-224
Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier (2022)
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models(bib)(pdf)(suppl)
39th International Conference on Machine Learning, July 17-23 2022, Baltimore, MD, USA
Alexander Tornede, Viktor Bengs, Eyke Hüllermeier (2022)
Machine Learning for Online Algorithm Selection under Censored Feedback(bib)
Thirty-Sixth AAAI Conference on Artificial Intelligence, February 22–March 1, 2022, Virtual
Arnab Sharma, Vitalik Melnikov, Eyke Hüllermeier, Heike Wehrheim (2022)
Property-Driven Testing of Black-Box Functions(bib)
2022 IEEE/ACM 10th International Conference on Formal Methods in Software Engineering (FormaliSE), 22-23 May 2022, Pittsburgh, PA, USA
Stefanie Schneider, Matthias Springstein, Javad Rahnama, Hubertus Kohle, Ralph Ewerth, Eyke Hüllermeier (2022)
iART - Eine Suchmaschine zur Unterstützung von bildorientierten Forschungsprozessen(bib)(pdf)
DHd 2022 Kulturen des digitalen Gedächtnisses. 8. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum", 7. - 11. März 2022, Potsdam
Pritha Gupta, Arunselvan Ramaswamy, Jan Peter Drees, Eyke Hüllermeier, Claudia Priesterjahn, Tibor Jager (2022)
Automated Information Leakage Detection: A New Method Combining Machine Learning and Hypothesis Testing with an Application to Side-channel Detection in Cryptographic Protocols(bib)(pdf)
14th International Conference on Agents and Artificial Intelligence (ICAART 2022), February 3-5, Virtual
Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencia, Johannes Fürnkranz, Michael Rapp (2022)
A flexible class of dependence-aware multi-label loss functions(bib)(pdf)
In: Machine Learning, Vol. 111, No. 2: pp. 713-737
Karlson Pfannschmidt, Pritha Gupta, Björn Haddenhorst, Eyke Hüllermeier (2022)
Learning context-dependent choice functions(bib)(preprint)
In: International Journal of Approximate Reasoning, Vol. 140: pp. 116-155
Vu-Linh Nguyen, Mohammad Hossein Shaker, Eyke Hüllermeier (2022)
How to measure uncertainty in uncertainty sampling for active learning(bib)(pdf)
In: Machine Learning, Vol. 111, No. 1: pp. 89-122

2021

Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier (2021)
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits(bib)(pdf)(suppl)
Advances in Neural Information Processing Systems, December 7 2021, Virtual
Julian Lienen, Eyke Hüllermeier (2021)
Credal Self-Supervised Learning(bib)(pdf)(suppl)
35th Conference on Neural Information Processing Systems (NeurIPS 2021), December 7, 2021, Virtual
Sadegh Abbaszadeh, Eyke Hüllermeier (2021)
Machine Learning With the Sugeno Integral: The Case of Binary Classification(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 29, No. 12: pp. 3723-3733
Robert Feldhans, Adrian Wilke, Stefan Heindorf, Mohammad Hossein Shaker, Barbara Hammer, Axel-Cyrille Ngonga Ngomo, Eyke Hüllermeier (2021)
Drift Detection in Text Data with Document Embeddings(bib)
Intelligent Data Engineering and Automated Learning – IDEAL 2021, November 25-27, 2021, Manchester, United Kingdom
Julian Lienen, Nils Nommensen, Ralph Ewerth, Eyke Hüllermeier (2021)
Robust Regression for Monocular Depth Estimation(bib)(pdf)(suppl)
Asian Conference on Machine Learning, November 17 - 19, 2021, Virtual
Jan Peter Drees, Pritha Gupta, Eyke Hüllermeier, Tibor Jager, Alexander Konze, Claudia Priesterjahn, Arunselvan Ramaswamy, Juraj Somorovsky (2021)
Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!(bib)
CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, 15. November 2021, Virtual Event, Republic of Korea
Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag (2021)
On the Identifiability of Hierarchical Decision Models(bib)
International Conference on Principles of Knowledge Representation and Reasoning, November 3-12, 2021, Virtual
Vu-Linh Nguyen, Eyke Hüllermeier (2021)
Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence(bib)(pdf)
In: Journal of Artificial Intelligence Research, Vol. 72: pp. 613-665
Matthias Springstein, Stefanie Schneider, Javad Rahnama, Eyke Hüllermeier, Hubertus Kohle, Ralph Ewerth (2021)
iART: A Search Engine for Art-Historical Images to Support Research in the Humanities(bib)(pdf)
29th ACM International Conference on Multimedia, October 20 - 24, 2021, Virtual
Clemens Damke, Eyke Hüllermeier (2021)
Ranking Structured Objects with Graph Neural Networks(bib)(preprint)
24th International Conference on Discovery Science (DS 2021), October 11–13, 2021, Halifax, NS, Canada, Virtual
Arunselvan Ramaswamy, Eyke Hüllermeier (2021)
Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis(bib)
In: IEEE Transactions on Artificial Intelligence: pp. 1-1
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier (2021)
Gradient-Based Label Binning in Multi-label Classification(bib)(preprint)
Machine Learning and Knowledge Discovery in Databases, September 13–17, 2021, Bilbao, Spain
Eyke Hüllermeier, Felix Mohr, Alexander Tornede, Marcel Wever (2021)
Automated Machine Learning, Bounded Rationality, and Rational Metareasoning(bib)(preprint)
ECMLPKDD Workshop on Automating Data Science (ADS2021), 17 September 2021, Virtual
Marcel Wever, Alexander Tornede, Felix Mohr, Eyke Hüllermeier (2021)
AutoML for Multi-Label Classification: Overview and Empirical Evaluation(bib)(pdf)
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, No. 9: pp. 3037-3054
Katharina J. Rohlfing, Philipp Cimiano, Ingrid Scharlau, Tobias Matzner, Heike M. Buhl, Hendrik Buschmeier, Elena Esposito, Angela Grimminger, Barbara Hammer, Reinhold Hab-Umbach, Ilona Horwath, Eyke Hüllermeier, Friederike Kern, Stefan Kopp, Kirsten Thommes, Axel-Cyrille Ngonga Ngomo, Carsten Schulte, Henning Wachsmuth, Petra Wagner, Britta Wrede (2021)
Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems(bib)(pdf)
In: IEEE Transactions on Cognitive and Developmental Systems, Vol. 13, No. 3: pp. 717-728
Patrick Kolpaczki, Viktor Bengs, Eyke Hüllermeier (2021)
Identifying Top-k Players in Cooperative Games via Shapley Bandits(bib)(pdf)
LWDA’21: Lernen, Wissen, Daten, Analysen, 1. - 3. September, 2021, Munich, Germany
Ruslan Bernijazov, Alexander Dicks, Roman Dumitrescu, Marc Foullois, Jonas Hanselle, Eyke Hüllermeier, Gökce Karakaya, Patrick Ködding, Volker Lohweg, Manuel Malatyali, Friedhelm Meyer Auf der Heide, Melina Panzner, Christian Soltenborn (2021)
A Meta-Review on Artificial Intelligence in Product Creation(bib)(pdf)
AI and Product Design Workshop, 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 19. August 2021, Montreal, Quebec, Canada
Björn Haddenhorst, Viktor Bengs, Jasmin Brandt, Eyke Hüllermeier (2021)
Testification of Condorcet Winners in dueling bandits(bib)(pdf)(suppl)
Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, July 27-30, 2021, Virtual
Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier (2021)
On testing transitivity in online preference learning(bib)(pdf)
In: Machine Learning, Vol. 110, No. 8: pp. 2063-2084
Felix Mohr, Marcel Wever (2021)
Replacing the Ex-Def Baseline in AutoML by Naive AutoML(bib)(pdf)(pres)
8th ICML Workshop on Automated Machine Learning, 2021-07-23, Virtual
Tanja Tornede, Alexander Tornede, Marcel Wever, Eyke Hüllermeier (2021)
Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance(bib)
GECCO '21, Proceedings of the Genetic and Evolutionary Computation Conference Companion, 10 - 14 July, 2021, Lille, France
Julian Lienen, Eyke Hüllermeier (2021)
Instance weighting through data imprecisiation(bib)
In: International Journal of Approximate Reasoning, Vol. 134: pp. 1-14
Ammar Shaker, Eyke Hüllermeier (2021)
TSK-Streams: learning TSK fuzzy systems for regression on data streams(bib)(pdf)
In: Data Mining and Knowledge Discovery, Vol. 35, No. 5: pp. 1941-1971
Julian Lienen, Eyke Hüllermeier, Ralph Ewerth, Nils Nommensen (2021)
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model(bib)
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 20-25 June 2021, Nashville, TN, USA
Andrea Campagner, Davide Ciucci, Eyke Hüllermeier (2021)
Rough set-based feature selection for weakly labeled data(bib)
In: International Journal of Approximate Reasoning, Vol. 136: pp. 150-167
Jonas Hanselle, Alexander Tornede, Marcel Wever, Eyke Hüllermeier (2021)
Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data(bib)(preprint)
In: Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty (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
Thomas Mortier, Marek Wydmuch, Krzysztof Dembczyński, Eyke Hüllermeier, Willem Waegeman (2021)
Efficient set-valued prediction in multi-class classification(bib)(preprint)
In: Data Mining and Knowledge Discovery, Vol. 35, No. 4: pp. 1435-1469
Sven Peeters, Vitalik Melnikov, Eyke Hüllermeier (2021)
Performance Prediction for Hardware-Software Configurations: A Case Study for Video Games(bib)
19th International Symposium on Intelligent Data Analysis, April 26–28, 2021, Porto, Portugal
Mohsen Ahmadi Fahandar, Eyke Hüllermeier (2021)
Analogical Embedding for Analogy-Based Learning to Rank(bib)
Advances in Intelligent Data Analysis XIX. IDA 2021, April 26-28, 2021, Porto, Portugal
Eyke Hüllermeier, Willem Waegeman (2021)
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods(bib)(pdf)
In: Machine Learning, Vol. 110, No. 3: pp. 457-506
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier (2021)
Learning Gradient Boosted Multi-label Classification Rules(bib)(preprint)
In: Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera (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
Daniel Weber, Stefan Heid, Henrik Bode, Jarren H. Lange, Eyke Hüllermeier, Oliver Wallscheid (2021)
Safe Bayesian Optimization for Data-Driven Power Electronics Control Design in Microgrids: From Simulations to Real-World Experiments(bib)(pdf)
In: IEEE Access, Vol. 9: pp. 35654-35669
Felix Mohr, Marcel Wever, Alexander Tornede, Eyke Hüllermeier (2021)
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning(bib)
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, No. 9: pp. 3055-3066
Felix Mohr, Viktor Bengs, Eyke Hüllermeier (2021)
Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model(bib)
AAAI Conference on Artificial Intelligence, February 2–9, 2021, Virtual
Julian Lienen, Eyke Hüllermeier (2021)
From Label Smoothing to Label Relaxation(bib)
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), February 2–9, 2021, Virtual
Viktor Bengs, Róbert Busa-Fekete, Adil El Mesaoudi-Paul, Eyke Hüllermeier (2021)
Preference-based Online Learning with Dueling Bandits: A Survey(bib)(pdf)
In: Journal of Machine Learning Research, Vol. 22, No. 7: pp. 1-108
Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag (2021)
Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals(bib)
Twenty-Ninth International Joint Conference on Artificial Intelligence, January 7-15, 2021, Yokohama, Japan (Virtual)
Stefanie Schneider, Matthias Springstein, Javad Rahnama, Eyke Hüllermeier, Ralph Ewerth, Hubertus Kohle (2021)
The Dissimilar in the Similar. An Attribute-guided Approach to the Subject-specific Classification of Art-historical Objects(bib)(pdf)
INFORMATIK 2020 - Back to the Future, 28 September - 2 October 2020, Virtual

2020

Alexander Tornede, Marcel Wever, Eyke Hüllermeier (2020)
Towards Meta-Algorithm Selection(bib)(pdf)
4th Workshop on Meta-Learning at NeurIPS, 11 December 2020, Virtual
Clemens Damke, Vitalik Melnikov, Eyke Hüllermeier (2020)
A Novel Higher-order Weisfeiler-Lehman Graph Convolution(bib)(pdf)(suppl)
12th Asian Conference on Machine Learning (ACML 2020), 18-20 November 2020, Bangkok, Thailand
Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, Eyke Hüllermeier (2020)
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis(bib)(pdf)
12th Asian Conference on Machine Learning (ACML 2020), 18-20 November 2020, Bangkok, Thailand
Stefan Heid, Arunselvan Ramaswamy, Eyke Hüllermeier (2020)
Constrained Multi-Agent Optimization with Unbounded Information Delay(bib)(pdf)
30. Workshop Computational Intelligence, 26. – 27. November 2020, Berlin, Germany
Simone Dari, Eyke Hüllermeier (2020)
Reliable Driver Gaze Classification based on Conformal Prediction(bib)(pdf)
30. Workshop Computational Intelligence, 26. – 27. November 2020, Berlin, Germany
Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencia, Johannes Fürnkranz (2020)
On Aggregation in Ensembles of Multilabel Classifiers(bib)(preprint)
23rd International Conference on Discovery Science, 19-21 October 2020, Virtual
Alexander Tornede, Marcel Wever, Eyke Hüllermeier (2020)
Extreme Algorithm Selection with Dyadic Feature Representation(bib)(preprint)
In: Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin (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
Stefan Heid, Daniel Weber, Henrik Bode, Eyke Hüllermeier, Oliver Wallscheid (2020)
OMG: A Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control(bib)(pdf)
In: Journal of Open Source Software (JOSS), Vol. 5, No. 54
Karlson Pfannschmidt, Eyke Hüllermeier (2020)
Learning Choice Functions via Pareto-Embeddings(bib)(preprint)
43rd German Conference on AI, 21-25 September, 2020, Bamberg, Germany
Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencia (2020)
Conformal Rule-Based Multi-label Classification(bib)(preprint)
KI 2020: Advances in Artificial Intelligence. 43rd German Conference on AI, September 21–25, 2020, Bamberg, Germany
Jonas Hanselle, Alexander Tornede, Marcel Wever, Eyke Hüllermeier (2020)
Hybrid Ranking and Regression for Algorithm Selection(bib)(preprint)
KI 2020: Advances in Artificial Intelligence. 43rd German Conference on AI, September 21–25, 2020, Bamberg, Germany
Eyke Hüllermeier (2020)
Towards Analogy-Based Explanations in Machine Learning(bib)(preprint)
Modeling Decisions for Artificial Intelligence, September 2–4, 2020, Sant Cugat, Spain
Tanja Tornede, Alexander Tornede, Marcel Wever, Felix Mohr, Eyke Hüllermeier (2020)
AutoML for Predictive Maintenance: One Tool to RUL Them All(bib)
Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, September 14-18, 2020, Ghent, Belgium
Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencia, Vu-Linh Nguyen, Michael Rapp (2020)
Rule-Based Multi-label Classification: Challenges and Opportunities(bib)
4th International Joint Conference on Rules and Reasoning, 29 June - 1 July 2020, Virtual
Simone Dari, Nikolay Kadrileev, Eyke Hüllermeier (2020)
A Neural Network-Based Driver Gaze Classification System with Vehicle Signals(bib)
2020 International Joint Conference on Neural Networks (IJCNN), 19-24 July 2020, Glasgow, UK
Viktor Bengs, Eyke Hüllermeier (2020)
Preselection Bandits(bib)(pdf)(suppl)
37th International Conference on Machine Learning, July 12-18 2020, Virtual
Andrea Campagner, Davide Ciucci, Eyke Hüllermeier (2020)
Feature Reduction in Superset Learning Using Rough Sets and Evidence Theory(bib)(pdf)
International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, 15-19 June 2020, Lisbon, Portugal
Javad Rahnama, Eyke Hüllermeier (2020)
Learning Tversky Similarity(bib)(pdf)
International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, 15-19 June 2020, Lisbon, Portugal
Marcel Wever, Lorijn van Rooijen, Heiko Hamann (2020)
Multioracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets(bib)
In: Evolutionary Computation, Vol. 28, No. 2: pp. 165-193
Katharina J. Rohlfing, Giuseppe Leonardi, Iris Nomikou, Joanna Raczaszek-Leonardi, Eyke Hüllermeier (2020)
Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches(bib)
In: IEEE Transactions on Cognitive and Developmental Systems, Vol. 12, No. 2: pp. 260-271
Henrik Bode, Stefan Heid, Daniel Weber, Eyke Hüllermeier, Oliver Wallscheid (2020)
Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control(bib)(pdf)
In: Journal of Open Source Software, Vol. 5, No. 54: pp. 2435
Adil El Mesaoudi-Paul, Dimitri Weiß, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney (2020)
Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach(bib)
In: Ilias S. Kotsireas, Panos M. Pardalos (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
Klaus Brinker, Eyke Hüllermeier (2020)
A Reduction of Label Ranking to Multiclass Classification(bib)
In: 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
Marcel Wever, Alexander Tornede, Felix Mohr, Eyke Hüllermeier (2020)
LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-label Classification(bib)(pdf)
In: Michael Berthold, Ad Feelders, Georg Krempl (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
Mohammad Hossein Shaker, Eyke Hüllermeier (2020)
Aleatoric and Epistemic Uncertainty with Random Forests(bib)(pdf)
International Symposium on Intelligent Data Analysis, April 27-29 2020, Bodenseeforum, Lake Constance, Germany
Cedric Richter, Eyke Hüllermeier, Marie-Christine Jakobs, Heike Wehrheim (2020)
Algorithm selection for software validation based on graph kernels(bib)(pdf)
In: Automated Software Engineering, Vol. 27, No. 1-2: pp. 153-186
Björn Haddenhorst, Eyke Hüllermeier, Martin Kolb (2020)
Generalized transitivity: A systematic comparison of concepts with an application to preferences in the Babington Smith model(bib)
In: International Journal of Approximate Reasoning, Vol. 119: pp. 373-407
Vu-Linh Nguyen, Eyke Hüllermeier (2020)
Reliable Multilabel Classification: Prediction with Partial Abstention(bib)
34th AAAI Conference on Artificial Intelligence, 7-12 Feburary 2020, New York, USA

2019

Sascha Henzgen, Eyke Hüllermeier (2019)
Mining Rank Data(bib)
In: ACM Transactions on Knowledge Discovery from Data, Vol. 13, No. 6: pp. 1-36
Eyke Hüllermeier, Sébastien Destercke, Ines Couso (2019)
Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants(bib)
In: Nahla Ben Amor, Benjamin Quost, Martin Theobald (eds.): Scalable Uncertainty Management. Lecture Notes in Computer Science; Vol. 11940. Cham: Springer. pp. 266-279
Marie-Luis Merten, Nina Seemann, Marcel Wever (2019)
Grammatikwandel digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff(bib)
In: Jahrbuch des Vereins für Niederdeutsche Sprachforschung = Niederdeutsches Jahrbuch, Vol. 142: pp. 124-146
Vitalik Melnikov, Eyke Hüllermeier (2019)
Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA(bib)(pdf)
11th Asian Conference on Machine Learning (ACML 2019), November 17 - 19, 2019, Nagoya, Japan
Alexander Tornede, Marcel Wever, Eyke Hüllermeier (2019)
Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking(bib)(pdf)
29. Workshop Computational Intelligence, 28. - 29. November 2019, Dortmund, Germany
Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier (2019)
Epistemic Uncertainty Sampling(bib)
In: Petra Kralj Novak, Tomislav Šmuc, Sašo Džeroski (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
Mohsen Ahmadi Fahandar, Eyke Hüllermeier (2019)
Feature Selection for Analogy-Based Learning to Rank(bib)
In: Petra Kralj Novak, Tomislav Šmuc, Sašo Džeroski (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
Felix Mohr, Marcel Wever, Alexander Tornede, Eyke Hüllermeier (2019)
From Automated to On-The-Fly Machine Learning(bib)(pdf)
In: Klaus David, Kurt Geihs, Martin Lange, Gerd Stumme (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; Vol. . Bonn: Gesellschaft für Informatik. pp. 273-274
Viktor Bengs, Matthias Eulert, Hajo Holzmann (2019)
Asymptotic confidence sets for the jump curve in bivariate regression problems(bib)
In: Journal of Multivariate Analysis, Vol. 173: pp. 291-312
Mohsen Ahmadi Fahandar, Eyke Hüllermeier (2019)
Analogy-Based Preference Learning with Kernels(bib)
In: Christoph Benzmüller, Heiner Stuckenschmidt (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
Vidal Kamdem Tagne, Siméon Fotso, Louis Aimé Fono, Eyke Hüllermeier (2019)
Choice Functions Generated by Mallows and Plackett–Luce Relations(bib)
In: New Mathematics and Natural Computation, Vol. 15, No. 2: pp. 191-213
Marcel Wever, Felix Mohr, Alexander Tornede, Eyke Hüllermeier (2019)
Automating Multi-Label Classification Extending ML-Plan(bib)(pdf)
6th ICML Workshop on Automated Machine Learning (AutoML 2019), June 14th 2019, Long Beach, California, USA
Willem Waegeman, Krzysztof Dembczyński, Eyke Hüllermeier (2019)
Multi-target prediction: a unifying view on problems and methods(bib)
In: Data Mining and Knowledge Discovery, Vol. 33, No. 2: pp. 293-324
Alexander Hetzer, Marcel Wever, Felix Mohr, Eyke Hüllermeier (2019)
Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking(bib)
ECDA 2019: European Conference on Data Analysis, 18 - 20 March 2019, Bayreuth, Germany
Marcel Wever, Felix Mohr, Eyke Hüllermeier, Alexander Hetzer (2019)
Towards Automated Machine Learning for Multi-Label Classification(bib)
ECDA 2019: European Conference on Data Analysis, 18 - 20 March 2019, Bayreuth, Germany
Ines Couso, Christian Borgelt, Eyke Hüllermeier, Rudolf Kruse (2019)
Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning(bib)
In: IEEE Computational Intelligence Magazine, Vol. 14, No. 1: pp. 31-44
Viktor Bengs, Hajo Holzmann (2019)
Adaptive confidence sets for kink estimation(bib)
In: Electronic Journal of Statistics, Vol. 13, No. 1: pp. 1523-1579

2018

Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier, Michael Rapp (2018)
Learning Interpretable Rules for Multi-Label Classification(bib)
In: Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven (eds.): Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning; Vol. . Cham: Springer. pp. 81-113
Dirk Schäfer, Eyke Hüllermeier (2018)
Preference-Based Reinforcement Learning Using Dyad Ranking(bib)
In: Larisa Soldatova, Joaquin Vanschoren, George Papadopoulos, Michelangelo Ceci (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
Felix Mohr, Marcel Wever, Eyke Hüllermeier (2018)
Reduction Stumps for Multi-class Classification(bib)
In: Wouter Duivesteijn, Arno Siebes, Antti Ukkonen (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
Felix Mohr, Marcel Wever, Eyke Hüllermeier (2018)
Automated Machine Learning Service Composition(bib)
Felix Mohr, Marcel Wever, Eyke Hüllermeier (2018)
ML-Plan: Automated machine learning via hierarchical planning(bib)
In: Machine Learning, Vol. 107, No. 8-10: pp. 1495-1515
Vitalik Melnikov, Eyke Hüllermeier (2018)
On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis(bib)
In: Machine Learning, Vol. 107, No. 8-10: pp. 1537-1560
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Eyke Hüllermeier (2018)
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty(bib)
Twenty-Seventh International Joint Conference on Artificial Intelligence, 13-19 July 2018, Stockholm, Sweden
Michael Hesse, Julia Timmermann, Eyke Hüllermeier, Ansgar Trächtler (2018)
A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart(bib)(pdf)
In: Procedia Manufacturing, Vol. 24: pp. 15-20
Felix Mohr, Marcel Wever, Eyke Hüllermeier, Amin Faez (2018)
(WIP) Towards the Automated Composition of Machine Learning Services(bib)
2018 IEEE International Conference on Services Computing (SCC), 2-7 July 2018, San Francisco, CA, USA
Felix Mohr, Marcel Wever, Eyke Hüllermeier (2018)
On-the-Fly Service Construction with Prototypes(bib)
2018 IEEE International Conference on Services Computing (SCC), 2-7 July 2018, San Francisco, CA, USA
Marcel Wever, Felix Mohr, Eyke Hüllermeier (2018)
Ensembles of evolved nested dichotomies for classification(bib)
GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference, July 15 - 19, 2018, Kyoto, Japan
Adil El Mesaoudi-Paul, Eyke Hüllermeier, Róbert Busa-Fekete (2018)
Ranking Distributions based on Noisy Sorting(bib)(pdf)
35th International Conference on Machine Learning, 10-15 July 2018, Stockholm, Sweden
Felix Mohr, Eyke Hüllermeier, Marcel Wever (2018)
ML-Plan for Unlimited-Length Machine Learning Pipelines(bib)(pdf)
ICML 2018 AutoML Workshop, 2018-07-10 – 2018-07-15, Stockholm, Sweden
Felix Mohr, Theodor Lettmann, Eyke Hüllermeier, Marcel Wever (2018)
Programmatic Task Network Planning(bib)
28th International Conference on Automated Planning and Scheduling, 2018-06-24 – 2018-06-29, Delft, Netherlands
Dirk Schäfer, Eyke Hüllermeier (2018)
Dyad ranking using Plackett–Luce models based on joint feature representations(bib)
In: Machine Learning, Vol. 107, No. 5: pp. 903-941
Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, Ke Yi (2018)
Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)(bib)(pdf)
In: Dagstuhl Manifestos, Vol. 7, No. 1: pp. 1-29
Nina Seemann, Michaela Geierhos, Marie-Luis Merten, Doris Tophinke, Marcel Wever, Eyke Hüllermeier (2018)
Supporting the Cognitive Process in Annotation Tasks(bib)
40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, 2018-03-07 – 2018-03-09, Stuttgart, Germany
Mohsen Ahmadi Fahandar, Eyke Hüllermeier (2018)
Learning to rank based on analogical reasoning(bib)
32nd AAAI Conference on Artificial Intelligence, 2-7 February 2018, New Orleans, Louisianna, USA

2017

Ammar Shaker, Waleri Heldt, Eyke Hüllermeier (2017)
Learning TSK Fuzzy Rules from Data Streams(bib)(pdf)
In: Michelangelo Ceci, Jaakko Hollmén, Sašo Džeroski, Ljupčo Todorovsk, Celine Vens, Sašo Džeroski (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
Eyke Hüllermeier (2017)
From knowledge-based to data-driven modeling of fuzzy rule-based systems: A critical reflection(bib)
Mohsen Ahmadi Fahandar, Eyke Hüllermeier (2017)
Learning to Rank based on Analogical Reasoning(bib)
Marcel Wever, Felix Mohr, Eyke Hüllermeier (2017)
Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization(bib)(pdf)
27th Workshop Computational Intelligence, 23. – 24. November 2017, Dortmund
Vitalik Melnikov, Eyke Hüllermeier (2017)
Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics(bib)(pdf)
In: Ralf Mikut, Eyke Hüllermeier, Frank Hoffmann (eds.): Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017; Vol. . Karlsruhe: KIT Scientific Publishing. pp. 1-12
Inés Couso, Eyke Hüllermeier (2017)
Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators(bib)
In: Frontiers in Computational Intelligence. Studies in Computational Intelligence; Vol. 739. Cham: Springer. pp. 31-46
Felix Mohr, Theo Lettmann, Eyke Hüllermeier (2017)
Planning with Independent Task Networks(bib)
In: Gabriele Kern-Isberner, Johannes Fürnkranz, Matthias Thimm (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
Inés Couso, Didier Dubois, Eyke Hüllermeier (2017)
Maximum Likelihood Estimation and Coarse Data(bib)
In: Serafín Moral, Olivier Pivert, Daniel Sánchez, Nicolás Marín (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
Mike Czech, Eyke Hüllermeier, Marie-Christine Jakobs, Heike Wehrheim (2017)
Predicting rankings of software verification tools(bib)
3rd ACM SIGSOFT International Workshop on Software Analytics, 4 September 2017, Paderborn, Germany
Marie C. Platenius, Ammar Shaker, Matthias Becker, Eyke Hüllermeier, Wilhelm Schafer (2017)
Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic(bib)
In: IEEE Transactions on Software Engineering, Vol. 43, No. 8: pp. 739-759
Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso (2017)
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening(bib)
34th International Conference on Machine Learning, Sydney, Australia
Nina Seemann, Marie-Luis Merten, Michaela Geierhos, Doris Tophinke, Eyke Hüllermeier (2017)
Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German(bib)(pdf)
Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, August, 2017, Vancouver, Canada
Ralph Ewerth, Matthias Springstein, Eric Müller, Alexander Balz, Jan Gehlhaar, Tolga Naziyok, Krzysztof Dembczyński, Eyke Hüllermeier (2017)
Estimating relative depth in single images via rankboost(bib)
2017 IEEE International Conference on Multimedia and Expo (ICME), 10-14 July 2017, Hong Kong
Marcel Wever, Lorijn van Rooijen, Heiko Hamann (2017)
Active coevolutionary learning of requirements specifications from examples(bib)
GECCO '17: Genetic and Evolutionary Computation Conference, July 15 - 19, 2017, Berlin, Germany
Michael Bräuning, Eyke Hüllermeier, Tobias Keller, Martin Glaum (2017)
Lexicographic preferences for predictive modeling of human decision making: A new machine learning method with an application in accounting(bib)
In: European Journal of Operational Research, Vol. 258, No. 1: pp. 295-306

2016

Mona Riemenschneider, Robin Senge, Ursula Neumann, Eyke Hüllermeier, Dominik Heider (2016)
Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification(bib)(pdf)
In: BioData Mining, Vol. 9
Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, Ke Yi (2016)
Research Directions for Principles of Data Management (Abridged)(bib)
In: SIGMOD Record, Vol. 45, No. 4: pp. 5–17
Aulon Shabani, Adil Paul, Radu Platon, Eyke Hüllermeier (2016)
Predicting the Electricity Consumption of Buildings: An Improved CBR Approach(bib)
In: Ashok Goel, M. Belén Díaz-Agudo, Thomas Roth-Berghofer (eds.): Case-Based Reasoning Research and Development. Lecture Notes in Computer Science; Vol. 9969. Cham: Springer. pp. 356-369
Vitalik Melnikov, Eyke Hüllermeier (2016)
Learning to Aggregate Using Uninorms(bib)(pdf)
In: Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken (eds.): Machine Learning and Knowledge Discovery in Databases. Lecture Notes in Computer Science; Vol. 9852. pp. 756-771
Krzysztof Dembczyński, Wojciech Kotłowski, Willem Waegeman, Róbert Busa-Fekete, Eyke Hüllermeier (2016)
Consistency of Probabilistic Classifier Trees(bib)(pdf)
In: Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken (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
Dirk Schäfer, Eyke Hüllermeier (2016)
Plackett-Luce Networks for Dyad Ranking(bib)(pdf)
LWDA 2016: Lernen, Wissen, Daten, Analysen 2016, September 12-14, 2016, Potsdam, Germany
Karlson Pfannschmidt, Eyke Hüllermeier, Susanne Held, Reto Neiger (2016)
Evaluating Tests in Medical Diagnosis: Combining Machine Learning with Game-Theoretical Concepts(bib)(pdf)
In: Joao Paulo Carvalho, Marie-Jeanne Lesot, Uzay Kaymak, Susana Vieira, Bernadette Bouchon-Meunier, Ronald R. Yager (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
Matthias Leinweber, Thomas Fober, Marc Strickert, Lars Baumgartner, Gerhard Klebe, Bernd Freisleben, Eyke Hüllermeier (2016)
CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites(bib)
In: IEEE Transactions on Knowledge and Data Engineering, Vol. 28, No. 6: pp. 1423-1434
Kalina Jasinska, Krzysztof Dembczynski, Róbert Busa-Fekete, Karlson Pfannschmidt, Timo Klerx, Eyke Hüllermeier (2016)
Extreme F-measure maximization using sparse probability estimates(bib)(pdf)
ICML'16: 33rd International Conference on International Conference on Machine Learning, June 19 - 24, 2016, New York, NY USA
Michael Bräuning, Eyke Hüllermeier (2016)
Learning Conditional Lexicographic Preference Tree(bib)(pdf)
In: Archives of data science. Series A, Vol. 1, No. 1: pp. 41-55
Vitalik Melnikov, Eyke Hüllermeier, Daniel Kaimann, Bernd Frick, Pritha Gupta (2016)
Pairwise versus Pointwise Ranking: A Case Study(bib)(pdf)
In: Schedae Informaticae, Vol. 25: pp. 73-83

2015

Eyke Hüllermeier (2015)
Does machine learning need fuzzy logic?(bib)
In: Fuzzy Sets and Systems, Vol. 281: pp. 292-299
Robin Senge, Eyke Hüllermeier (2015)
Fast Fuzzy Pattern Tree Learning for Classification(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 23, No. 6: pp. 2024-2033
Eyke Hüllermeier (2015)
From knowledge-based to data-driven fuzzy modeling(bib)
In: Informatik-Spektrum, Vol. 38, No. 6: pp. 500-509
Baiÿzs Szörényi, Róbert Busa-Fekete, Adil Paul, Eyke Hüllermeier (2015)
Online F-measure optimization(bib)(pdf)
NIPS'15: 28th International Conference on Neural Information Processing Systems, December 7 - 12, 2015, Montreal Canada
Baiÿzs Szörényi, Róbert Busa-Fekete, Adil Paul, Eyke Hüllermeier (2015)
Online rank elicitation for Plackett-Luce: a dueling bandits approach(bib)(pdf)
NIPS'15: 28th International Conference on Neural Information Processing Systems, December 7 - 12, 2015, Montreal Canada
Amira Abdel-Aziz, Eyke Hüllermeier (2015)
Case Base Maintenance in Preference-Based CBR(bib)
In: Eyke Hüllermeier, Mirjam Minor (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
Ralph Ewerth, Alexander Balz, Jan Gehlhaar, Krzysztof Dembczyński, Eyke Hüllermeier (2015)
Depth Estimation in Monocular Images: Quantitative versus Qualitative Approaches(bib)(pdf)
In: Frank Hoffmann, Eyke Hüllermeier (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
Shenzhen Lu, Eyke Hüllermeier (2015)
Locally weighted regression through data imprecisiation(bib)(pdf)
In: Frank Hoffmann, Eyke Hüllermeier (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
Dirk Schäfer, Eyke Hüllermeier (2015)
Preference-based meta-learning using dyad ranking: recommending algorithms in cold-start situations(bib)
MetaSel'15: International Conference on Meta-Learning and Algorithm Selection, 7 September 2015, Porto Portugal
Adil Paul, Eyke Hüllermeier (2015)
A CBR Approach to the Angry Birds Game(bib)
Twenty-Third International Conference on Case-Based Reasoning (ICCBR 2015), September 28-30, 2015, Frankfurt, Germany
Dirk Schäfer, Eyke Hüllermeier (2015)
Dyad Ranking Using A Bilinear Plackett-Luce Model(bib)
In: Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, João Gama, Alípio Jorge, Carlos Soares (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
Sascha Henzgen, Eyke Hüllermeier (2015)
Weighted Rank Correlation: A Flexible Approach Based on Fuzzy Order Relations(bib)
In: 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
Eyke Hüllermeier, Weiwei Cheng (2015)
Superset Learning Based on Generalized Loss Minimization(bib)
In: 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
Santiago Garcia-Jimenez, Humberto Bustince, Eyke Hüllermeier, Radko Mesiar, Nikhil R. Pal, Ana Pradera (2015)
Overlap Indices: Construction of and Application to Interpolative Fuzzy Systems(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 23, No. 4: pp. 1259-1273
Balázs Szörényi, Róbert Busa-Fekete, Paul Weng, Eyke Hüllermeier (2015)
Qualitative Multi-Armed Bandits: A Quantile-Based Approach(bib)(pdf)
32nd International Conference on Machine Learning, July 6 - 11, 2015, Lille, France
Ammar Shaker, Eyke Hüllermeier (2015)
Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study(bib)
In: Neurocomputing, Vol. 150, No. A: pp. 250-264

2014

Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier (2014)
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm(bib)
In: Machine Learning, Vol. 97, No. 3: pp. 327-351
Michiel Stock, Thomas Fober, Eyke Hüllermeier, Serghei Glinca, Gerhard Klebe, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman (2014)
Identification of Functionally Related Enzymes by Learning-to-Rank Methods(bib)
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 11, No. 6: pp. 1157-1169
Willem Waegeman, Krzysztof Dembczyński, Arkadiusz Jachnik, Weiwei Cheng, Eyke Hüllermeier (2014)
On the Bayes-Optimality of F-Measure Maximizers(bib)(pdf)
In: Journal of Machine Learning Research, Vol. 15: pp. 3513-3568
Róbert Busa-Fekete, Eyke Hüllermeier (2014)
A Survey of Preference-Based Online Learning with Bandit Algorithms(bib)
In: Peter Auer, Alexander Clark, Thomas Zeugmann, Sandra Zilles (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
Eyke Hüllermeier (2014)
Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization(bib)
In: International Journal of Approximate Reasoning, Vol. 55, No. 7: pp. 1519-1534
Eyke Hüllermeier (2014)
Rejoinder on “Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization”(bib)
In: International Journal of Approximate Reasoning, Vol. 55, No. 7: pp. 1609-1613
Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo (2014)
Guest Editors’ introduction: special issue of the ECML/PKDD 2014 journal track(bib)
In: Machine Learning, Vol. 97, No. 1-2: pp. 1-3
Marc Strickert, Kerstin Bunte, Frank-Michael Schleif, Eyke Hüllermeier (2014)
Correlation-based embedding of pairwise score data(bib)
In: Neurocomputing, Vol. 141: pp. 97-109
Sascha Henzgen, Eyke Hüllermeier (2014)
Mining Rank Data(bib)
In: Sašo Džeroski, Panče Panov, Dragi Kocev, Ljupčo Todorovski (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
Georg Krempl, Indre Žliobaite, Dariusz Brzeziński, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski (2014)
Open challenges for data stream mining research(bib)
In: ACM SIGKDD Explorations Newsletter, Vol. 16, No. 1: pp. 1-10
Amira Abdel-Aziz, Marc Strickert, Eyke Hüllermeier (2014)
Learning Solution Similarity in Preference-Based CBR(bib)
In: Luc Lamontagne, Enric Plaza (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
Timo Krotzky, Thomas Fober, Eyke Hüllermeier, Gerhard Klebe (2014)
Extended Graph-Based Models for Enhanced Similarity Search in Cavbase(bib)
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 11, No. 5: pp. 878-890
Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo (2014)
Guest editors’ introduction: special issue of the ECML/PKDD 2014 journal track(bib)
In: Data Mining and Knowledge Discovery, Vol. 28, No. 5-6: pp. 1129-1133
Sascha Henzgen, Marc Strickert, Eyke Hüllermeier (2014)
Visualization of evolving fuzzy rule-based systems(bib)
In: Evolving Systems, Vol. 5, No. 3: pp. 175-191
Róbert Busa-Fekete, Balázs Szörényi, Eyke Hüllermeier (2014)
PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences(bib)
28th AAAI Conference on Artificial Intelligence (AAAI-14), Jul 2014, Quebec City, Canada
Róbert Busa-Fekete, Eyke Hüllermeier, Balázs Szörényi (2014)
Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows(bib)(pdf)
31st International Conference on Machine Learning (ICML 2014), 21-26 June, 2014, Beijing, China
Ali Fallah Tehrani, Marc Strickert, Eyke Hüllermeier (2014)
The Choquet kernel for monotone data(bib)
22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 23-25 April 2014, Bruges (Belgium)
Manish Agarwal, Ali Fallah Tehrani, Eyke Hüllermeier (2014)
Preference-based Learning of Ideal Solutions in TOPSIS-like Decision Models(bib)
In: Journal of Multi-Criteria Decision Analysis, Vol. 22, No. 3-4: pp. 175-183
Ammar Shaker, Eyke Hüllermeier (2014)
Survival analysis on data streams: Analyzing temporal events in dynamically changing environments(bib)
In: International Journal of Applied Mathematics and Computer Science, Vol. 24, No. 1: pp. 199-212
Elena Montañes, Robin Senge, Jose Barranquero, José Ramón Quevedo, Juan José del Coz, Eyke Hüllermeier (2014)
Dependent binary relevance models for multi-label classification(bib)
In: Pattern Recognition, Vol. 47, No. 3: pp. 1494-1508
Marco Mernberger, Daniel Moog, Simone Stork, Stefan Zauner, Uwe G. Maier, Eyke Hüllermeier (2014)
Protein Sub-Cellular Localization Prediction for Special Compartments via Optimized Time Series Distances(bib)
In: Journal of Bioinformatics and Computational Biology, Vol. 12, No. 1: pp. 1350016
Norbert Donner-Banzhoff, Jörg Haasenritter, Eyke Hüllermeier, Annika Viniol, Stefan Bösner, Annette Becker (2014)
The comprehensive diagnostic study is suggested as a design to model the diagnostic process(bib)
In: Journal of Clinical Epidemiology, Vol. 67, No. 2: pp. 124-132
Robin Senge, Stefan Bösner, Krzysztof Dembczyński, Jörg Haasenritter, Oliver Hirsch, Norbert Donner-Banzhoff, Eyke Hüllermeier (2014)
Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty(bib)
In: Information Sciences, Vol. 255: pp. 16-29

2013

Stefan Bösner, Katharina Bönisch, Jörg Haasenritter, Patrice Schlegel, Eyke Hüllermeier, Norbert Donner-Banzhoff (2013)
Chest pain in primary care: is the localization of pain diagnostically helpful in the critical evaluation of patients? - A cross sectional study(bib)
In: BMC Family Practice, Vol. 14
Sascha Henzgen, Eyke Hüllermeier (2013)
Weighted Rank Correlation Measures Based on Fuzzy Order Relations(bib)(pdf)
In: Frank Hoffmann, Eyke Hüllermeier (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
Robin Senge, Juan José Del Coz, Eyke Hüllermeier (2013)
On the Problem of Error Propagation in Classifier Chains for Multi-label Classification(bib)
In: Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning (eds.): Data Analysis, Machine Learning and Knowledge Discovery. Studies in Classification, Data Analysis, and Knowledge Organization; Vol. . Cham: Springer. pp. 163-170
György Szarvas, Róbert Busa-Fekete, Eyke Hüllermeier (2013)
Learning to Rank Lexical Substitutions(bib)(pdf)
2013 Conference on Empirical Methods in Natural Language Processing, 18-21 October 2013, Seattle, Washington, USA
Weiwei Cheng, Sascha Henzgen, Eyke Hüllermeier (2013)
Labelwise versus Pairwise Decomposition in Label Ranking(bib)
LWA 2013. Lernen, Wissen & Adaptivität, 7.-9. October 2013, Bamberg, Germany
Ali Fallah Tehrani, Eyke Hüllermeier (2013)
Ordinal Choquistic Regression(bib)
8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2013), 11 - 13 September 2013, Milan, Italy
Paul Weng, Róbert Busa-Fekete, Eyke Hüllermeier (2013)
Interactive Q-Learning with Ordinal Rewards and Unreliable Tutor(bib)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2013). Reinforcement Learning with Generalized Feedback, 23rd September 2013, Prague
Paul Weng, Róbert Busa-Fekete, Eyke Hüllermeier (2013)
Preference-based Evolutionary Direct Policy Search(bib)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2013). Reinforcement Learning with Generalized Feedback, 23rd September 2013, Prague
Ammar Shaker, Eyke Hüllermeier (2013)
Event history analysis on data streams: An application to earthquake occurence(bib)
RealStream 2013, 1st International Workshop on Real-World Challenges for Data Stream Mining, September 27, 2013, Prague, Czech Republic
Dominik Heider, Robin Senge, Weiwei Cheng, Eyke Hüllermeier (2013)
Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistance prediction(bib)
In: Bioinformatics, Vol. 29, No. 16: pp. 1946-1952
Weiwei Cheng, Eyke Hüllermeier (2013)
A Nearest Neighbor Approach to Label Ranking based on Generalized Labelwise Loss Minimization(bib)
7th Multidisciplinary Workshop on Advances in Preference Handling (M-PREF '13), August 3-5, 2013, Beijing, China
Eyke Hüllermeier, Weiwei Cheng (2013)
Preference-Based CBR: General Ideas and Basic Principles(bib)
In: Francesca Rossi (eds.): Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, Beijing, China, 3 - 9 August 2013, Vol. 4; Vol. . Palo Alto, Calif.: AAAI Press. pp. 3012-3016
Thomas Fober, Gerhard Klebe, Eyke Hüllermeier (2013)
Local Clique Merging: An Extension of the Maximum Common Subgraph Measure with Applications in Structural Bioinformatics(bib)
In: Berthold Lausen, Dirk van den Poel, Alfred Ultsch (eds.): Algorithms from and for Nature and Life. Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization; Vol. . Cham: Springer. pp. 279-286
Maryam Nasiri, Thomas Fober, Robin Senge, Eyke Hüllermeier (2013)
Fuzzy pattern trees as an alternative to rule-based fuzzy systems: Knowledge-driven, data-driven and hybrid modeling of color yield in polyester dyeing(bib)
2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 24-28 June 2013, Edmonton, AB, Canada
Krzysztof Dembczyński, Arkadiusz Jachnik, Wojciech Kotlowski, Willem Waegeman, Eyke Hüllermeier (2013)
Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization(bib)(pdf)
ICML'13: 30th International Conference on International Conference on Machine Learning, June 16 - 21, 2013, Atlanta GA USA
Róbert Busa-Fekete, Balázs Szörényi, Weiwei Cheng, Paul Weng, Eyke Hüllermeier (2013)
Top-k Selection based on Adaptive Sampling of Noisy Preferences(bib)(pdf)
ICML'13: 30th International Conference on International Conference on Machine Learning, June 16 - 21, 2013, Atlanta GA USA
Ammar Shaker, Eyke Hüllermeier (2013)
Recovery Analysis for Adaptive Learning from Non-stationary Data Streams(bib)
In: Robert Burduk, Konrad Jackowski, Marek Kurzynski, Michał Wozniak, Andrzej Zolnierek (eds.): Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing; Vol. 226. pp. 289-298
Sascha Henzgen, Marc Strickert, Eyke Hüllermeier (2013)
Rule Chains for Visualizing Evolving Fuzzy Rule-Based Systems(bib)
In: Robert Burduk, Konrad Jackowski, Marek Kurzynski, Michał Wozniak, Andrzej Zolnierek (eds.): Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing; Vol. 226. pp. 279-288
Ammar Shaker, Robin Senge, Eyke Hüllermeier (2013)
Evolving fuzzy pattern trees for binary classification on data streams(bib)
In: Information Sciences, Vol. 220: pp. 34-45
Jörg Haasenritter, Annika Viniol, Annette Becker, Stefan Bösner, Eyke Hüllermeier, Robin Senge, Norbert Donner-Banzhoff (2013)
Diagnose im Kontext – eine erweiterte Perspektive(bib)
In: Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, Vol. 107, No. 9-10: pp. 585-591
Eyke Hüllermeier, Ali Fallah Tehrani (2013)
Efficient Learning of Classifiers Based on the 2-Additive Choquet Integral(bib)
In: Christian Moewes, Andreas Nürnberger (eds.): Computational Intelligence in Intelligent Data Analysis. Studies in Computational Intelligence; Vol. 445. Berlin, Heidelberg: Springer. pp. 17-29

2012

Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman, Volkmar Welker (2012)
Label Ranking with Partial Abstention based on Thresholded Probabilistic Models(bib)(pdf)
25. NIPS 2012, December 3-8, 2012, Lake Tahoe, Nevada, USA
Ammar Shaker, Eyke Hüllermeier (2012)
IBLStreams: a system for instance-based classification and regression on data streams(bib)
In: Evolving Systems, Vol. 3, No. 4: pp. 235-249
Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier (2012)
Preference Learning Using the Choquet Integral: The Case of Multipartite Ranking(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 20, No. 6: pp. 1102-1113
M. Dolores Ruiz, Eyke Hüllermeier (2012)
A formal and empirical analysis of the fuzzy gamma rank correlation coefficient(bib)
In: Information Sciences, Vol. 206: pp. 1-17
Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier (2012)
Learning monotone nonlinear models using the Choquet integral(bib)
In: Machine Learning, Vol. 89, No. 1-2: pp. 183-211
Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park (2012)
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm(bib)
In: Machine Learning, Vol. 89, No. 1-2: pp. 123-156
Frank Hoffmann, Eyke Hüllermeier, Andreas Kroll (2012)
Ausgewählte Beiträge des GMA-Fachausschusses 5.14 “Computational Intelligence”(bib)
In: at - Automatisierungstechnik, Vol. 60, No. 10: pp. 587-588
Robin Senge, Thomas Fober, Maryam Nasiri, Eyke Hüllermeier (2012)
Fuzzy Pattern Trees: Ein alternativer Ansatz zur Fuzzy-Modellierung(bib)
In: at - Automatisierungstechnik, Vol. 60, No. 10: pp. 622-629
Weiwei Cheng, Eyke Hüllermeier (2012)
Probability Estimation for Multi-class Classification Based on Label Ranking(bib)
In: Peter A. Flach, Tijl De Bie, Nello Cristianini (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
Krzysztof Dembczyński, Willem Waegeman, Eyke Hüllermeier (2012)
An Analysis of Chaining in Multi-Label Classification(bib)
In: Luc De Raedt, Christian Bessiere, Didier Dubois, Patrick Doherty, Paolo Frasconi, Fredrik Heintz, Peter Lucas (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
Eyke Hüllermeier, Ali Fallah Tehrani (2012)
On the VC-Dimension of the Choquet Integral(bib)
In: Salvatore Greco, Bernadette Bouchon-Meunier, Gulianella Coletti, Mario Fedrizzi, Benedetto Matarazzo, Ronald R. Yager (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
Krzysztof Dembczyński, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier (2012)
On label dependence and loss minimization in multi-label classification(bib)(pdf)
In: Machine Learning, Vol. 88, No. 1-2: pp. 5-45
Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier (2012)
Fingerprint Kernels for Protein Structure Comparison(bib)
In: Molecular Informatics, Vol. 31, No. 6-7: pp. 443-452
Matthias Leinweber, Lars Baumgärtner, Marco Mernberger, Thomas Fober, Eyke Hüllermeier, Gerhard Klebe, Bernd Freisleben (2012)
GPU-based Cloud computing for comparing the structure of protein binding sites(bib)
2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST), 18-20 June 2012, Campione d'Italia, Italy
Krzysztof Dembczyński, Wojciech Kotłowski, Eyke Hüllermeier (2012)
Consistent multilabel ranking through univariate loss minimization(bib)(pdf)
ICML'12: 29th International Conference on Machine Learning, 26 June 2012- 1 July 2012, Edinburgh, Scotland, UK
Eyke Hüllermeier, Maria Rifqi, Sascha Henzgen, Robin Senge (2012)
Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 20, No. 3: pp. 546-556
Humberto Bustince, Miguel Pagola, Radko Mesiar, Eyke Hüllermeier, Francisco Herrera (2012)
Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 20, No. 3: pp. 405-415
Eyke Hüllermeier (2012)
Fuzzy Rules in Data Mining: From Fuzzy Associations to Gradual Dependencies(bib)
In: Enric Trillas, Piero P. Bonissone, Luis Magdalena, Janusz Kacprz (eds.): Combining Experimentation and Theory. A Hommage to Abe Mamdani. Studies in Fuzziness and Soft Computing; Vol. 271. pp. 123-135

2011

Oliver Hirsch, Stefan Bösner, Eyke Hüllermeier, Robin Senge, Krzysztof Dembczynski, Norbert Donner-Banzhoff (2011)
Multivariate modeling to identify patterns in clinical data: the example of chest pain(bib)
In: BMC Medical Research Methodology, Vol. 11
Thomas Fober, Gerghei Glinca, Gerhard Klebe, Eyke Hüllermeier (2011)
Superposition and Alignment of Labeled Point Clouds(bib)
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 8, No. 6: pp. 1653-1666
Eyke Hüllermeier, Johannes Fürnkranz (2011)
Learning from Label Preferences(bib)
In: Tapio Elomaa, Jaakko Hollmén, Heikki Mannila (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
Eyke Hüllermeier, Patrice Schlegel (2011)
Preference-Based CBR: First Steps toward a Methodological Framework(bib)
In: Ashwin Ram, Nirmalie Wiratunga (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
Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier (2011)
SEGA: Semiglobal Graph Alignment for Structure-Based Protein Comparison(bib)
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 8, No. 5: pp. 1330-1343
Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park (2011)
Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning(bib)
In: Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis (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
Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier (2011)
Choquistic Regression: Generalizing Logistic Regression using the Choquet Integral(bib)
EUSFLAT - LFA 2011, 18 - 22 July 2011, Aix-Les-Bains, France
Edwin Lughofer, Eyke Hüllermeier (2011)
On-line Redundancy Elimination in Evolving Fuzzy Regression Models using a Fuzzy Inclusion Measure(bib)
EUSFLAT - LFA 2011, 18 - 22 July 2011, Aix-Les-Bains, France
Eyke Hüllermeier (2011)
Fuzzy machine learning and data mining(bib)
In: WIREs: Data Mining and Knowledge Discovery, Vol. 1, No. 4: pp. 269-283
Carmel Domshlak, Eyke Hüllermeier, Souhila Kaci, Henri Prade (2011)
Preferences in AI: An overview(bib)
In: Artificial Intelligence, Vol. 175, No. 7-8: pp. 1037-1052
Robin Senge, Eyke Hüllermeier (2011)
Top-Down Induction of Fuzzy Pattern Trees(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 19, No. 2: pp. 241-252
Eyke Hüllermeier (2011)
Fuzzy sets in machine learning and data mining(bib)(pdf)
In: Applied Soft Computing, Vol. 11, No. 2: pp. 1493-1505

2010

Hyung-Won Koh, Eyke Hüllermeier (2010)
Mining Gradual Dependencies Based on Fuzzy Rank Correlation(bib)
In: Christian Borgel (eds.): Combining Soft Computing and Statistical Methods in Data Analysis. Advances in Intelligent and Soft Computing; Vol. 77. Berlin, Heidelberg: Springer. pp. 379-386
Patrick Pfeffer, Thomas Fober, Eyke Hüllermeier, Gerhard Klebe (2010)
GARLig: A Fully Automated Tool for Subset Selection of Large Fragment Spaces via a Self-Adaptive Genetic Algorithm(bib)
In: Journal of Chemical Information and Modeling, Vol. 50, No. 9: pp. 1644-1659
Eyke Hüllermeier (2010)
Uncertainty in Clustering and Classification(bib)
In: Amol Deshpande, Anthony Hunter (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
Johannes Fürnkranz, Eyke Hüllermeier (2010)
Preference Learning and Ranking by Pairwise Comparison(bib)
In: Johannes Fürnkranz, Eyke Hüllermeier (eds.): Preference Learning; Vol. . Berlin, Heidelberg: Springer. pp. 65-82
Johannes Fürnkranz, Eyke Hüllermeier (2010)
Preference Learning: An Introduction(bib)
In: Johannes Fürnkranz, Eyke Hüllermeier (eds.): Preference Learning; Vol. . Berlin: Springer. pp. 1-17
Weiwei Cheng, Michaël Rademaker, Bernard De Baets, Eyke Hüllermeier (2010)
Predicting Partial Orders: Ranking with Abstention(bib)
In: José Luis Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag (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
Krzysztof Dembczyński, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier (2010)
Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss(bib)
In: José Luis Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag (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
Robin Senge, Eyke Hüllermeier (2010)
Pattern trees for regression and fuzzy systems modeling(bib)
2010 IEEE International Conference on Fuzzy Systems (FUZZ‐IEEE 2010), 18-23 July 2010, Barcelona, Spain
Thomas Fober, Eyke Hüllermeier (2010)
Similarity measures for protein structures based on fuzzy histogram comparison(bib)
International Conference on Fuzzy Systems, 18-23 July 2010, Barcelona, Spain
Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier (2010)
Graded multilabel classification: the ordinal case(bib)
ICML '10: 27th International Conference on Machine Learning, June 21 - 24, 2010, Haifa, Israel
Eyke Hüllermeier, Johannes Fürnkranz (2010)
On predictive accuracy and risk minimization in pairwise label ranking(bib)
In: Journal of Computer and System Sciences, Vol. 76, No. 1: pp. 49-62
Eyke Hüllermeier, Stijn Vanderlooy (2010)
Combining predictions in pairwise classification: An optimal adaptive voting strategy and its relation to weighted voting(bib)
In: Pattern Recognition, Vol. 43, No. 1: pp. 128-142
Jens Christian Hühn, Eyke Hüllermeier (2010)
An Analysis of the FURIA Algorithm for Fuzzy Rule Induction(bib)
In: Jacek Koronacki, Zbigniew W. Raś, Sławomir T. Wierzchoń, Janusz Kacprzyk (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

2009

Frank Hoffmann, Eyke Hüllermeier (2009)
Multiple Geometrical Alignments for the Analysis of Protein Active Sites(bib)(pdf)
19. Workshop Computational Intelligence, 2. - 4. Dezember 2009, Dortmund
Jens Hühn, Eyke Hüllermeier (2009)
FURIA: an algorithm for unordered fuzzy rule induction(bib)
In: Data Mining and Knowledge Discovery, Vol. 19, No. 3: pp. 293-319
Eyke Hüllermeier, S. Vanderlooy (2009)
Why Fuzzy Decision Trees are Good Rankers(bib)
In: IEEE Transactions on Fuzzy Systems, Vol. 17, No. 6: pp. 1233-1244
Thomas Fober, Gerhard Klebe, Eyke Hüllermeier (2009)
Efficient Construction of Multiple Geometrical Alignments for the Comparison of Protein Binding Sites(bib)
2009 Ninth International Conference on Intelligent Systems Design and Applications, 30 Nov.-2 Dec. 2009, Pisa, Italy
Imen Boukhris, Zied Elouedi, Thomas Fober, Marco Mernberger, Eyke Hüllermeier (2009)
Similarity Analysis of Protein Binding Sites: A Generalization of the Maximum Common Subgraph Measure Based on Quasi-Clique Detection(bib)
2009 Ninth International Conference on Intelligent Systems Design and Applications, 30 Nov.-2 Dec. 2009, Pisa, Italy
Weiwei Cheng, Eyke Hüllermeier (2009)
Combining Instance-Based Learning and Logistic Regression for Multilabel Classification(bib)
LWA 2009: Workshop-Woche: Lernen, Wissen, Adaptivität, 21.-23. September 2009, Darmstadt, Germany
Thomas Fober, Marco Mernberger, Vitalik Melnikov, Ralph Moritz, Eyke Hüllermeier (2009)
Extension and Empirical Comparison of Graph-Kernels for the Analysis of Protein Active Sites(bib)
LWA 2009: Workshop-Woche: Lernen, Wissen, Adaptivität, 21.-23. September 2009, Darmstadt, Germany
Robin Senge, Eyke Hüllermeier (2009)
Learning Pattern Tree Classifiers Using a Co-Evolutionary Algorithm(bib)
LWA 2009: Workshop-Woche: Lernen, Wissen, Adaptivität, 21.-23. September 2009, Darmstadt, Germany
Weiwei Cheng, Eyke Hüllermeier (2009)
Combining instance-based learning and logistic regression for multilabel classification(bib)
In: Machine Learning, Vol. 76, No. 2-3: pp. 211-225
Johannes Fürnkranz, Eyke Hüllermeier, Stijn Vanderlooy (2009)
Binary Decomposition Methods for Multipartite Ranking(bib)
In: Wray Buntine, Marko Grobelnik, Dunja Mladenić, John Shawe-Taylor (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
Weiwei Cheng, Eyke Hüllermeier (2009)
Combining Instance-Based Learning and Logistic Regression for Multilabel Classification(bib)
In: Wray Buntine, Marko Grobelnik, Dunja Mladenić, John Shawe-Taylor (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
Nils Weskamp, Eyke Hüllermeier, Gerhard Klebe (2009)
Merging chemical and biological space: Structural mapping of enzyme binding pocket space(bib)
In: Proteins: Structure, Function, and Bioinformatics, Vol. 76, No. 2: pp. 317-330
Weiwei Cheng, Jens Hühn, Eyke Hüllermeier (2009)
Decision tree and instance-based learning for label ranking(bib)
ICML '09: 26th Annual International Conference on Machine Learning, June 14 - 18, 2009, Montreal Quebec, Canada
Weiwei Cheng, Eyke Hüllermeier (2009)
A New Instance-Based Label Ranking Approach Using the Mallows Model(bib)
In: Wen Yu, Haibo He, Nian Zhang (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
Eyke Hüllermeier (2009)
On the Usefulness of Fuzzy Sets in Data Mining(bib)
In: 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

2008

Eyke Hüllermeier, Ilya Vladimirskiy, Belén Prados Suárez, Eva Stauch (2008)
Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions(bib)
In: Klaus-Dieter Althoff, Ralph Bergmann, Mirjam Minor, Alexandre Hanft (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
Weiwei Cheng, Eyke Hüllermeier (2008)
Learning Similarity Functions from Qualitative Feedback(bib)
In: Klaus-Dieter Althoff, Ralph Bergmann, Mirjam Minor, Alexandre Hanft (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
Stijn Vanderlooy, Eyke Hüllermeier (2008)
A Critical Analysis of Variants of the AUC(bib)
In: Walter Daelemans, Bart Goethals, Katharina Morik (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
Eyke Hüllermeier (2008)
Granular Computing in Machine Learning and Data Mining(bib)
In: Witold Pedrycz, Andrzej Skowron, Vladik Kreinovich (eds.): Handbook of Granular Computing; Vol. . pp. 889-906
Eyke Hüllermeier (2008)
Fuzzy Methods for Data Mining and Machine Learning: State of the Art and Prospects(bib)
In: Humberto Bustince, Francisco Herrera, Javier Montero (eds.): Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Studies in Fuzziness and Soft Computing; Vol. 220. Berlin, Heidelberg: Springer. pp. 357-375
Eyke Hüllermeier, Johannes Fürnkranz (2008)
Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants(bib)
In: Giacomo Della Riccia, Didier Dubois, Rudolf Kruse, Hans-Joachim Lenz (eds.): Preferences and Similarities. CISM International Centre for Mechanical Sciences; Vol. 504. Vienna: Springer. pp. 283-304
Eyke Hüllermeier (2008)
Why Fuzzy Set Theory is Useful in Data Mining(bib)
In: Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire (eds.): Successes and New Directions in Data Mining; Vol. . Hershey ; New York: Information Science Reference. pp. 1-16

2007

Eyke Hüllermeier, Johannes Fürnkranz (2007)
On Minimizing the Position Error in Label Ranking(bib)
In: Joost N. Kok, Jacek Koronacki, Raomon Lopez de Mantaras, Stan Matwin, Dunja Mladenič, Andrzej Skowron (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
Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyke Hüllermeier (2007)
On Pairwise Naive Bayes Classifiers(bib)
In: Joost N. Kok, Jacek Koronacki, Raomon Lopez de Mantaras, Stan Matwin, Dunja Mladenič, Andrzej Skowron (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
Jürgen Beringer, Eyke Hüllermeier (2007)
An Efficient Algorithm for Instance-Based Learning on Data Streams(bib)
In: Petra Perner (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
Klaus Brinker, Eyke Hüllermeier (2007)
Label Ranking in Case-Based Reasoning(bib)
In: Rosina O. Weber, Michael M. Richter (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
Jurgen Beringer, Eyke Hüllermeier (2007)
Adaptive Optimization of the Number of Clusters in Fuzzy Clustering(bib)
2007 IEEE International Fuzzy Systems Conference, 23-26 July 2007, London, UK
Eyke Hüllermeier, Nils Weskamp, Gerhard Klebe, Daniel Kuhn (2007)
Graph Alignment: Fuzzy Pattern Mining for the Structural Analysis of Protein Active Sites(bib)
2007 IEEE International Fuzzy Systems Conference, 23-26 July 2007, London, UK
Jürgen Beringer, Eyke Hüllermeier (2007)
Fuzzy Clustering of Parallel Data Streams(bib)
In: Jose Valente de Oliveira, Witold Pedrycz (eds.): Advances in Fuzzy Clustering and its Applications; Vol. . Chichester: Wiley. pp. 333-352

2006

Korinna Bade, Eyke Hüllermeier, Andreas Nurnberger (2006)
Hierarchical Classification by Expected Utility Maximization(bib)
6th IEEE International Conference on Data Mining, 18-22 December, 2006, Hong Kong, China
Ulrich Bodenhofer, Eyke Hüllermeier, Frank Klawonn, Rudolf Kruse (2006)
Special Issue on Soft Computing for Information Mining(bib)
In: Soft Computing, Vol. 11, No. 5: pp. 397-399
Iman Karimi, Eyke Hüllermeier, Konstantin Meskouris (2006)
A fuzzy-probabilistic earthquake risk assessment system(bib)
In: Soft Computing, Vol. 11, No. 3: pp. 229-238
Klaus Brinker, Eyke Hüllermeier (2006)
Case-Based Label Ranking(bib)
In: Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou (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
Eyke Hüllermeier (2006)
The Choquet-Integral as an Aggregation Operator in Case-Based Learning(bib)
In: Bernd Reusch (eds.): Computational Intelligence, Theory and Applications. International Conference 9th Fuzzy Days in Dortmund, Germany, Sept. 18–20, 2006 Proceedings; Vol. . Berlin, Heidelberg: Springer. pp. 615-627
Didier Dubois, Eyke Hüllermeier, Henri Prade (2006)
Fuzzy methods for case-based recommendation and decision support(bib)
In: Journal of Intelligent Information Systems, Vol. 27, No. 2: pp. 95-115

2005

Eyke Hüllermeier, Jürgen Beringer (2005)
Learning from Ambiguously Labeled Examples(bib)
In: A. Fazel Famili, Joost N. Kok, José M. Peña, Arno Siebes, Ad Feelders (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
Eyke Hüllermeier, Johannes Fürnkranz (2005)
Learning Label Preferences: Ranking Error Versus Position Error(bib)
In: A. Fazel Famili, Joost N. Kok, José M. Peña, Arno Siebes, Ad Feelders (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
Didier Dubois, Eyke Hüllermeier (2005)
A Notion of Comparative Probabilistic Entropy Based on the Possibilistic Specificity Ordering(bib)
In: 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
Eyke Hüllermeier (2005)
Fuzzy Methods in Knowledge Discovery(bib)
In: Bernd Reusch (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

2004

Eyke Hüllermeier, J. Fürnkranz (2004)
Ranking by pairwise comparison a note on risk minimization(bib)
2004 IEEE International Conference on Fuzzy Systems, 25-29 July, 2004, Budapest, Hungary

2003

Eyke Hüllermeier (2003)
Instance-Based Learning of Credible Label Sets(bib)
In: Andreas Günter, Rudolf Kruse, Bernd Neumann (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
Johannes Fürnkranz, Eyke Hüllermeier (2003)
Pairwise Preference Learning and Ranking(bib)
In: Nada Lavrač, Dragan Gamberger, Hendrik Blockeel, Ljupčo Todorovski (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
Eyke Hüllermeier (2003)
Regularized Learning with Flexible Constraints(bib)
In: Michael R. Berthold, Hans-Joachim Lenz, Elizabeth Bradley, Rudolf Kruse, Christian Borgelt (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
Didier Dubois, Eyke Hüllermeier, Henri Prade (2003)
A Note on Quality Measures for Fuzzy Association Rules(bib)
In: Taner Bilgiç, Bernard De Baets, Okyay 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
Eyke Hüllermeier (2003)
Inducing Fuzzy Concepts through Extended Version Space Learning(bib)
In: Taner Bilgiç, Bernard De Baets, Okyay 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. 677-684
Eyke Hüllermeier (2003)
A Method for Predicting Solutions in Case-Based Problem Solving(bib)
In: Enrico Blanzieri, Luigi Portinale (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
Didier Dubois, Eyke Hüllermeier, Henri Prade (2003)
Flexible Control of Case-Based Prediction in the Framework of Possibility Theory(bib)
In: Enrico Blanzieri, Luigi Portinale (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
Didier Dubois, Eyke Hüllermeier, Henri Prade (2003)
Possibilistic case-based decisions(bib)
In: Cédric Lesage, Marie Cottrell (eds.): Connectionist Approaches in Economics and Management Sciences. Advances in Computational Management Science; Vol. 6. Boston, MA: Springer. pp. 31-48
Eyke Hüllermeier (2003)
Sequential Decision Making in Heuristic Search(bib)
In: Giacomo Della Riccia, Didier Dubois, Rudolf Kruse, Hans-J. Lenz (eds.): Planning Based on Decision Theory. International Centre for Mechanical Sciences; Vol. 472. Vienna: Springer. pp. 27-41

2002

Eyke Hüllermeier (2002)
Possibilistic Induction in Decision-Tree Learning(bib)
In: Tapio Elomaa, Heikki Mannila, Hannu Toivonen (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
Eyke Hüllermeier (2002)
Association Rules for Expressing Gradual Dependencies(bib)
In: Tapio Elomaa, Heikki Mannila, Hannu Toivonen (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
Eyke Hüllermeier (2002)
Experience-Based Decision Making and Learning from Examples(bib)
In: Operations Research Proceedings 2001. Selected Papers of the International Conference on Operations Research (OR 2001) Duisburg, September 3–5, 2001; Vol. . Berlin, Heidelberg: Springer. pp. 363-370
Martine de Calmes, Didier Dubois, Eyke Hüllermeier, Henri Prade, Florence Sedes (2002)
Case-based querying and prediction: a fuzzy set approach(bib)
2002 IEEE World Congress on Computational Intelligence, 12-17 May 2002, Honolulu, HI, USA
Eyke Hüllermeier (2002)
Exploiting similarity and experience in decision making(bib)
In: Proceedings of the 2002 IEEE International Conference on Fuzzy Systems: May 12 - 17, 2002, Hilton Hawaiian Village Hotel, Honolulu, Hawaii. Vol. 1; Vol. . Piscataway, NJ: IEEE. pp. 729-734
Eyke Hüllermeier, Didier Dubois, Henri Prade (2002)
Knowledge-Based Extrapolation of Cases: A Possibilistic Approach(bib)
In: Bernadette Bouchon-Meunier, Julio Gutiérrez-Ríos, Luis Magdalena, Ronald R. Yager (eds.): Technologies for Constructing Intelligent Systems 1. Studies in Fuzziness and Soft Computing; Vol. 89. Heidelberg: Physica Verlag. pp. 377-390

2001

Eyke Hüllermeier (2001)
Fuzzy Association Rules: Semantic Issues and Quality Measures(bib)
In: Bernd Reusch (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
Eyke Hüllermeier (2001)
Implication-Based Fuzzy Association Rules(bib)
In: 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
Didier Dubois, Eyke Hüllermeier, Henri Prade (2001)
Toward the representation of implication-based fuzzy rules in terms of crisp rules(bib)
20th NAFIPS International Conference, 25-28 July 2001, Vancouver, BC, Canada

1999

Eyke Hüllermeier (1999)
Exploiting Similarity for Supporting Data Analysis and Problem Solving(bib)
In: David J. Hand, Joost N. Kok, Michael R. Berthold (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
Eyke Hüllermeier (1999)
A Possibilistic Formalization of Case-Based Reasoning and Decision Making(bib)
In: Bernd Reusch (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

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