Eyke Hüllermeier

605 papers A* 61A 25B 35C 21Misc 6Journal 302Unranked 132

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Aleatoric and Epistemic Uncertainty Measures for Ordinal Classification Through Binary Reduction. Mach. Learn. Stefan Haas, Eyke Hüllermeier
2026	J	`jnl`	Distribution Matching for Graph Quantification Under Structural Covariate Shift. CoRR Clemens Damke, Eyke Hüllermeier
2026	J	`jnl`	Efficient Credal Prediction through Decalibration. CoRR Paul Hofman, Timo Löhr, Maximilian Muschalik, Yusuf Sale, Eyke Hüllermeier
2026	J	`jnl`	Evolutionary Mapping of Neural Networks to Spatial Accelerators. CoRR Alessandro Pierro, Jonathan Timcheck, Jason Yik, Marius Lindauer, Eyke Hüllermeier, Marcel Wever
2026	A*	`conf`	Fine-grained Uncertainty Decomposition in Large Language Models: A Spectral Approach. AAAI Nassim Walha, Sebastian G. Gruber, Thomas Decker, Yinchong Yang, Alireza Javanmardi, Eyke Hüllermeier, Florian Buettner
2026	J	`jnl`	Linear-LLM-SCM: Benchmarking LLMs for Coefficient Elicitation in Linear-Gaussian Causal Models. CoRR Kanta Yamaoka, Sumantrak Mukherjee, Thomas Gärtner, David Antony Selby, Stefan Konigorski, Eyke Hüllermeier, Viktor Bengs, Sebastian Josef Vollmer
2026	J	`jnl`	Quantification of Credal Uncertainty: A Distance-Based Approach. CoRR Xabier Gonzalez-Garcia, Siu Lun Chau, Julian Rodemann, Michele Caprio, Krikamol Muandet, Humberto Bustince, Sébastien Destercke, Eyke Hüllermeier, Yusuf Sale
2026	A*	`conf`	Shapley Value Approximation Based on k-Additive Games. AAAI Guilherme Dean Pelegrina, Patrick Kolpaczki, Eyke Hüllermeier
2026	A*	`conf`	Uncertainty Quantification for Machine Learning: One Size Does Not Fit All. AAAI Paul Hofman, Yusuf Sale, Eyke Hüllermeier
2026	J	`jnl`	Uncertainty Quantification in Pairwise Difference Learning for Classification. Mach. Learn. Mohamed Karim Belaid, Maximilian Rabus, Eyke Hüllermeier
2025	J	`jnl`	A Survey of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier
2025	J	`jnl`	A calibration test for evaluating set-based epistemic uncertainty representations. CoRR Mira Jürgens, Thomas Mortier, Eyke Hüllermeier, Viktor Bengs, Willem Waegeman
2025	J	`jnl`	A calibration test for evaluating set-based epistemic uncertainty representations. Mach. Learn. Mira Jürgens, Thomas Mortier, Eyke Hüllermeier, Viktor Bengs, Willem Waegeman
2025	—	`conf`	Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection. NAACL (Long Papers) Maximilian Spliethöver, Tim Knebler, Fabian Fumagalli, Maximilian Muschalik, Barbara Hammer, Eyke Hüllermeier, Henning Wachsmuth
2025	J	`jnl`	Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection. CoRR Maximilian Spliethöver, Tim Knebler, Fabian Fumagalli, Maximilian Muschalik, Barbara Hammer, Eyke Hüllermeier, Henning Wachsmuth
2025	J	`jnl`	Adjusted Count Quantification Learning on Graphs. CoRR Clemens Damke, Eyke Hüllermeier
2025	J	`jnl`	Aleatoric and Epistemic Uncertainty Measures for Ordinal Classification through Binary Reduction. CoRR Stefan Haas, Eyke Hüllermeier
2025	—	`conf`	Aleatoric and Epistemic Uncertainty in Conformal Prediction. COPA Yusuf Sale, Alireza Javanmardi, Eyke Hüllermeier
2025	J	`jnl`	All You Need for Counterfactual Explainability Is Principled and Reliable Estimate of Aleatoric and Epistemic Uncertainty. CoRR Kacper Sokol, Eyke Hüllermeier
2025	J	`jnl`	An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression. CoRR Christopher Bülte, Yusuf Sale, Timo Löhr, Paul Hofman, Gitta Kutyniok, Eyke Hüllermeier
2025	—	`conf`	Antithetic Sampling for Top-K Shapley Identification. xAI (2) Patrick Kolpaczki, Tim Nielen, Eyke Hüllermeier
2025	J	`jnl`	Antithetic Sampling for Top-k Shapley Identification. CoRR Patrick Kolpaczki, Tim Nielen, Eyke Hüllermeier
2025	J	`jnl`	Co-Exploration and Co-Exploitation via Shared Structure in Multi-Task Bandits. CoRR Sumantrak Mukherjee, Serafima Lebedeva, Valentin Margraf, Jonas Hanselle, Kanta Yamaoka, Viktor Bengs, Stefan Konigorski, Eyke Hüllermeier, Sebastian Josef Vollmer
2025	A*	`conf`	Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries. ICML Xuening Feng, Zhaohui Jiang, Timo Kaufmann, Eyke Hüllermeier, Paul Weng, Yifei Zhu
2025	J	`jnl`	Conformal Prediction Regions are Imprecise Highest Density Regions. CoRR Michele Caprio, Yusuf Sale, Eyke Hüllermeier
2025	J	`jnl`	Conformal Prediction in Hierarchical Classification. CoRR Thomas Mortier, Alireza Javanmardi, Yusuf Sale, Eyke Hüllermeier, Willem Waegeman
2025	A	`conf`	Conformal Prediction without Nonconformity Scores. UAI Jonas Hanselle, Alireza Javanmardi, Tobias Florin Oberkofler, Yusuf Sale, Eyke Hüllermeier
2025	—	`conf`	Conformal prediction regions are imprecise highest density regions. ISIPTA Michele Caprio, Yusuf Sale, Eyke Hüllermeier
2025	J	`jnl`	Conformalized prescriptive machine learning for uncertainty-aware automated decision making: the case of goodwill requests. Int. J. Data Sci. Anal. Stefan Haas, Eyke Hüllermeier
2025	J	`jnl`	Credal Prediction based on Relative Likelihood. CoRR Timo Löhr, Paul Hofman, Felix Mohr, Eyke Hüllermeier
2025	A*	`conf`	DUO: Diverse, Uncertain, On-Policy Query Generation and Selection for Reinforcement Learning from Human Feedback. AAAI Xuening Feng, Zhaohui Jiang, Timo Kaufmann, Puchen Xu, Eyke Hüllermeier, Paul Weng, Yifei Zhu
2025	J	`jnl`	Data-Driven Probabilistic Evaluation of Logic Properties with PAC-Confidence on Mealy Machines. CoRR Swantje Plambeck, Ali Salamati, Eyke Hüllermeier, Görschwin Fey
2025	—	`conf`	Distribution Matching for Graph Quantification Under Structural Covariate Shift. ECML/PKDD (2) Clemens Damke, Eyke Hüllermeier
2025	J	`jnl`	Efficient Online Learning with Predictive Coding Networks: Exploiting Temporal Correlations. CoRR Darius Masoum Zadeh-Jousdani, Elvin Hajizada, Eyke Hüllermeier
2025	A*	`conf`	Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks. ICLR Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto, Janine Strotherm, Luca Hermes, Alessandro Sperduti, Eyke Hüllermeier, Barbara Hammer
2025	J	`jnl`	Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks. CoRR Fabian Fumagalli, Maximilian Muschalik, Paolo Frazzetto, Janine Strotherm, Luca Hermes, Alessandro Sperduti, Eyke Hüllermeier, Barbara Hammer
2025	—	`conf`	Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration for Exosuit Personalization. ECML/PKDD (8) Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio
2025	J	`jnl`	Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions. CoRR Hubert Baniecki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Przemyslaw Biecek
2025	J	`jnl`	Feedback Forensics: A Toolkit to Measure AI Personality. CoRR Arduin Findeis, Timo Kaufmann, Eyke Hüllermeier, Robert Mullins
2025	J	`jnl`	Fine-Grained Uncertainty Decomposition in Large Language Models: A Spectral Approach. CoRR Nassim Walha, Sebastian G. Gruber, Thomas Decker, Yinchong Yang, Alireza Javanmardi, Eyke Hüllermeier, Florian Buettner
2025	J	`jnl`	Information leakage detection through approximate Bayes-optimal prediction. Inf. Sci. Pritha Gupta, Marcel Wever, Eyke Hüllermeier
2025	A*	`conf`	Inverse Constitutional AI: Compressing Preferences into Principles. ICLR Arduin Findeis, Timo Kaufmann, Eyke Hüllermeier, Samuel Albanie, Robert Mullins
2025	J	`jnl`	Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues. CoRR Leandra Fichtel, Maximilian Spliethöver, Eyke Hüllermeier, Patricia Jimenez, Nils Oliver Klowait, Stefan Kopp, Axel-Cyrille Ngonga Ngomo, Amelie Sophie Robrecht, Ingrid Scharlau, Lutz Terfloth, Anna-Lisa Vollmer, Henning Wachsmuth
2025	—	`conf`	Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions. EMNLP (Findings) Meghdut Sengupta, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Debanjan Ghosh, Henning Wachsmuth
2025	J	`jnl`	Is Your Prompt Safe? Investigating Prompt Injection Attacks Against Open-Source LLMs. CoRR Jiawen Wang, Pritha Gupta, Ivan Habernal, Eyke Hüllermeier
2025	—	`conf`	MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making. xAI (3) Stefan Heid, Jaroslaw Kornowicz, Jonas Hanselle, Kirsten Thommes, Eyke Hüllermeier
2025	J	`jnl`	Optimal Conformal Prediction under Epistemic Uncertainty. CoRR Alireza Javanmardi, Soroush H. Zargarbashi, Santo M. A. R. Thies, Willem Waegeman, Aleksandar Bojchevski, Eyke Hüllermeier
2025	J	`jnl`	Probabilistic scoring lists for interpretable machine learning. Mach. Learn. Jonas Hanselle, Stefan Heid, Johannes Fürnkranz, Eyke Hüllermeier
2025	J	`jnl`	Random Forest Calibration. CoRR Mohammad Hossein Shaker, Eyke Hüllermeier
2025	J	`jnl`	Random forest calibration. Knowl. Based Syst. Mohammad Hossein Shaker, Eyke Hüllermeier
2025	J	`jnl`	Real-time Continual Learning on Intel Loihi 2. CoRR Elvin Hajizada, Danielle Rager, Timothy Shea, Leobardo Campos-Macias, Andreas Wild, Eyke Hüllermeier, Yulia Sandamirskaya, Mike Davies
2025	J	`jnl`	ResponseRank: Data-Efficient Reward Modeling through Preference Strength Learning. CoRR Timo Kaufmann, Yannick Metz, Daniel A. Keim, Eyke Hüllermeier
2025	J	`jnl`	Shapley Value Approximation Based on k-Additive Games. CoRR Guilherme Dean Pelegrina, Patrick Kolpaczki, Eyke Hüllermeier
2025	A	`conf`	SynthACticBench: A Capability-Based Synthetic Benchmark for Algorithm Configuration. GECCO Valentin Margraf, Anna Lappe, Marcel Wever, Carolin Benjamins, Eyke Hüllermeier, Marius Lindauer
2025	J	`jnl`	Uncertainty Estimation of Lake Ice Cover Maps From a Random Forest Classifier Using MODIS TOA Reflectance Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Nastaran Saberi, Mohammad Hossein Shaker, Claude R. Duguay, Katharine Andrea Scott, Eyke Hüllermeier
2025	J	`jnl`	Uncertainty Quantification for Machine Learning: One Size Does Not Fit All. CoRR Paul Hofman, Yusuf Sale, Eyke Hüllermeier
2025	J	`jnl`	Uncertainty Quantification for Regression: A Unified Framework based on kernel scores. CoRR Christopher Bülte, Yusuf Sale, Gitta Kutyniok, Eyke Hüllermeier
2025	J	`jnl`	Uncertainty Quantification with Proper Scoring Rules: Adjusting Measures to Prediction Tasks. CoRR Paul Hofman, Yusuf Sale, Eyke Hüllermeier
2025	J	`jnl`	Uncertainty quantification in ordinal classification: A comparison of measures. Int. J. Approx. Reason. Stefan Haas, Eyke Hüllermeier
2025	A	`conf`	Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory. AISTATS Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer, Julia Herbinger
2025	A*	`conf`	X-Hacking: The Threat of Misguided AutoML. ICML Rahul Sharma, Sumantrak Mukherjee, Andrea Sipka, Eyke Hüllermeier, Sebastian Josef Vollmer, Sergey Redyuk, David Antony Selby
2024	—	`conf`	A Novel Bayes' Theorem for Upper Probabilities. Epi UAI Michele Caprio, Yusuf Sale, Eyke Hüllermeier, Insup Lee
2024	J	`jnl`	ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data. CoRR Valentin Margraf, Marcel Wever, Sandra Gilhuber, Gabriel Marques Tavares, Thomas Seidl, Eyke Hüllermeier
2024	J	`jnl`	An Extensive Analysis of Different Approaches to Driver Gaze Classification. IEEE Trans. Intell. Transp. Syst. Simone Camberg, Eyke Hüllermeier
2024	A*	`conf`	Approximating the Shapley Value without Marginal Contributions. AAAI Patrick Kolpaczki, Viktor Bengs, Maximilian Muschalik, Eyke Hüllermeier
2024	A*	`conf`	Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO. IJCAI Jasmin Brandt, Marcel Wever, Viktor Bengs, Eyke Hüllermeier
2024	A*	`conf`	Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. AAAI Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2024	J	`jnl`	Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. CoRR Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2024	—	`conf`	CUQ-GNN: Committee-Based Graph Uncertainty Quantification Using Posterior Networks. ECML/PKDD (8) Clemens Damke, Eyke Hüllermeier
2024	J	`jnl`	CUQ-GNN: Committee-based Graph Uncertainty Quantification using Posterior Networks. CoRR Clemens Damke, Eyke Hüllermeier
2024	A*	`conf`	Conformalized Credal Set Predictors. NeurIPS Alireza Javanmardi, David Stutz, Eyke Hüllermeier
2024	J	`jnl`	Conformalized Credal Set Predictors. CoRR Alireza Javanmardi, David Stutz, Eyke Hüllermeier
2024	J	`jnl`	Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 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	—	`conf`	Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning. ECML/PKDD (1) Amihossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei
2024	J	`jnl`	Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration. CoRR Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio
2024	—	`conf`	Explaining Change in Models and Data with Global Feature Importance and Effects. TempXAI@PKDD/ECML Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2024	—	`conf`	How Much Can Stratification Improve the Approximation of Shapley Values? xAI (2) Patrick Kolpaczki, Georg Haselbeck, Eyke Hüllermeier
2024	A	`conf`	Identifying Copeland Winners in Dueling Bandits with Indifferences. AISTATS Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
2024	J	`jnl`	Information Leakage Detection through Approximate Bayes-optimal Prediction. CoRR Pritha Gupta, Marcel Wever, Eyke Hüllermeier
2024	J	`jnl`	Inverse Constitutional AI: Compressing Preferences into Principles. CoRR Arduin Findeis, Timo Kaufmann, Eyke Hüllermeier, Samuel Albanie, Robert Mullins
2024	A*	`conf`	Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? ICML Mira Jürgens, Nis Meinert, Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2024	J	`jnl`	Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? CoRR Mira Jürgens, Nis Meinert, Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2024	A*	`conf`	KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions. ICML Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer
2024	J	`jnl`	KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions. CoRR Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer
2024	A	`conf`	Label-wise Aleatoric and Epistemic Uncertainty Quantification. UAI Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier
2024	J	`jnl`	Label-wise Aleatoric and Epistemic Uncertainty Quantification. CoRR Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier
2024	J	`jnl`	Learning decision catalogues for situated decision making: The case of scoring systems. Int. J. Approx. Reason. Stefan Heid, Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier
2024	A	`conf`	Linear Opinion Pooling for Uncertainty Quantification on Graphs. UAI Clemens Damke, Eyke Hüllermeier
2024	J	`jnl`	Linear Opinion Pooling for Uncertainty Quantification on Graphs. CoRR Clemens Damke, Eyke Hüllermeier
2024	A*	`conf`	Mitigating Label Noise through Data Ambiguation. AAAI Julian Lienen, Eyke Hüllermeier
2024	J	`jnl`	OCALM: Object-Centric Assessment with Language Models. CoRR Timo Kaufmann, Jannis Blüml, Antonia Wüst, Quentin Delfosse, Kristian Kersting, Eyke Hüllermeier
2024	J	`jnl`	On the efficient implementation of classification rule learning. Adv. Data Anal. Classif. Michael Rapp, Johannes Fürnkranz, Eyke Hüllermeier
2024	—	`conf`	Pairwise Difference Learning for Classification. DS (2) Mohamed Karim Belaid, Maximilian Rabus, Eyke Hüllermeier
2024	J	`jnl`	Pairwise Difference Learning for Classification. CoRR Mohamed Karim Belaid, Maximilian Rabus, Eyke Hüllermeier
2024	J	`jnl`	Piecewise-Stationary Dueling Bandits. Trans. Mach. Learn. Res. Patrick Kolpaczki, Eyke Hüllermeier, Viktor Bengs
2024	A*	`conf`	Position: Why We Must Rethink Empirical Research in Machine Learning. ICML Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2024	J	`jnl`	Position: Why We Must Rethink Empirical Research in Machine Learning. CoRR Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rügamer, Eyke Hüllermeier, Anne-Laure Boulesteix, Bernd Bischl
2024	J	`jnl`	Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies - part II. 4OR Eyke Hüllermeier, Roman Slowinski
2024	J	`jnl`	Preference learning and multiple criteria decision aiding: differences, commonalities, and synergies-part I. 4OR Eyke Hüllermeier, Roman Slowinski
2024	J	`jnl`	Probabilistic Scoring Lists for Interpretable Machine Learning. CoRR Jonas Hanselle, Stefan Heid, Johannes Fürnkranz, Eyke Hüllermeier
2024	A*	`conf`	Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization. ICLR Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei
2024	J	`jnl`	Problem Solving Through Human-AI Preference-Based Cooperation. CoRR Subhabrata Dutta, Timo Kaufmann, Goran Glavas, Ivan Habernal, Kristian Kersting, Frauke Kreuter, Mira Mezini, Iryna Gurevych, Eyke Hüllermeier, Hinrich Schütze
2024	—	`ed.`	Proceedings of the First Multimodal, Affective and Interactive eXplainable AI Workshop (MAI-XAI24 2024) co-located with 27th European Conference On Artificial Intelligence 19-24 October 2024 (ECAI 2024), Santiago de Compostela, Spain, October 19, 2024. MAI-XAI@ECAI Jose Maria Alonso-Moral, Zach Anthis, Rafael Berlanga, Alejandro Catalá, Philipp Cimiano, Peter Flach, Eyke Hüllermeier, Tim Miller, Oana Mitrut, Dimitry Mindlin, Gabriela Moise, Alin Moldoveanu, Florica Moldoveanu, Kacper Sokol, Aitor Soroa
2024	—	`ed.`	Proceedings of the Workshop on Explainable AI for Time Series and Data Streams (TempXAI 2024) co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, September 9th, 2024. TempXAI@PKDD/ECML Zahraa S. Abdallah, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Matthias Jakobs, Emmanuel Müller, Maximilian Muschalik, Panagiotis Papapetrou, Amal Saadallah, George Tzagkarakis
2024	J	`jnl`	Quantifying Aleatoric and Epistemic Uncertainty with Proper Scoring Rules. CoRR Paul Hofman, Yusuf Sale, Eyke Hüllermeier
2024	J	`jnl`	Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction. J. Data Min. Digit. Humanit. Stefan Heid, Marcel Wever, Eyke Hüllermeier
2024	A	`conf`	SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. AISTATS Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2024	J	`jnl`	SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. CoRR Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2024	A*	`conf`	Second-Order Uncertainty Quantification: A Distance-Based Approach. ICML Yusuf Sale, Viktor Bengs, Michele Caprio, Eyke Hüllermeier
2024	J	`jnl`	Second-Order Uncertainty Quantification: Variance-Based Measures. CoRR Yusuf Sale, Paul Hofman, Lisa Wimmer, Eyke Hüllermeier, Thomas Nagler
2024	J	`jnl`	Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments. Frontiers Artif. Intell. Stefan Haas, Konstantin Hegestweiler, Michael Rapp, Maximilian Muschalik, Eyke Hüllermeier
2024	—	`conf`	Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification. AIME (2) Timo Löhr, Michael Ingrisch, Eyke Hüllermeier
2024	J	`jnl`	Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory. CoRR Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer, Julia Herbinger
2024	—	`conf`	Unsupervised Class Incremental Learning using Empty Classes. BMVC Workshops Svenja Uhlemeyer, Julian Lienen, Youssef Shoeb, Eyke Hüllermeier, Hanno Gottschalk
2024	A*	`conf`	shapiq: Shapley Interactions for Machine Learning. NeurIPS Maximilian Muschalik, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara Hammer, Eyke Hüllermeier
2024	J	`jnl`	shapiq: Shapley Interactions for Machine Learning. CoRR Maximilian Muschalik, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara Hammer, Eyke Hüllermeier
2023	J	`jnl`	A Novel Bayes' Theorem for Upper Probabilities. CoRR Michele Caprio, Yusuf Sale, Eyke Hüllermeier, Insup Lee
2023	A*	`conf`	A Survey of Methods for Automated Algorithm Configuration (Extended Abstract). IJCAI Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2023	J	`jnl`	A Survey of Reinforcement Learning from Human Feedback. CoRR Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier
2023	A*	`conf`	AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. AAAI Jasmin Brandt, Elias Schede, Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2023	J	`jnl`	Algorithm selection on a meta level. Mach. Learn. Alexander Tornede, Lukas Gehring, Tanja Tornede, Marcel Wever, Eyke Hüllermeier
2023	J	`jnl`	Approximating the Shapley Value without Marginal Contributions. CoRR Patrick Kolpaczki, Viktor Bengs, Eyke Hüllermeier
2023	B	`conf`	Automated Side-Channel Attacks using Black-Box Neural Architecture Search. ARES Pritha Gupta, Jan Peter Drees, Eyke Hüllermeier
2023	J	`jnl`	Automated Side-Channel Attacks using Black-Box Neural Architecture Search. IACR Cryptol. ePrint Arch. Pritha Gupta, Jan Peter Drees, Eyke Hüllermeier
2023	—	`conf`	Compare-xAI: Toward Unifying Functional Testing Methods for Post-hoc XAI Algorithms into a Multi-dimensional Benchmark. xAI (2) Mohamed Karim Belaid, Richard Bornemann, Maximilian Rabus, Ralf Krestel, Eyke Hüllermeier
2023	—	`conf`	Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain. LWDA Jonas Hanselle, Jaroslaw Kornowicz, Stefan Heid, Kirsten Thommes, Eyke Hüllermeier
2023	—	`conf`	Conformal Credal Self-Supervised Learning. COPA Julian Lienen, Caglar Demir, Eyke Hüllermeier
2023	—	`conf`	Conformal Prediction with Partially Labeled Data. COPA Alireza Javanmardi, Yusuf Sale, Paul Hofman, Eyke Hüllermeier
2023	J	`jnl`	Conformal Prediction with Partially Labeled Data. CoRR Alireza Javanmardi, Yusuf Sale, Paul Hofman, Eyke Hüllermeier
2023	—	`conf`	Contextual Preselection Methods in Pool-based Realtime Algorithm Configuration. LWDA Jasmin Brandt, Elias Schede, Shivam Sharma, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2023	J	`jnl`	Continual Learning: Applications and the Road Forward. CoRR 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
2023	A	`conf`	Cooperative Co-Evolution for Ensembles of Nested Dichotomies for Multi-Class Classification. GECCO Marcel Wever, Miran Özdogan, Eyke Hüllermeier
2023	J	`jnl`	Detecting Novelties with Empty Classes. CoRR Svenja Uhlemeyer, Julian Lienen, Eyke Hüllermeier, Hanno Gottschalk
2023	J	`jnl`	Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning. CoRR Amirhossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei
2023	J	`jnl`	Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning. SIAM J. Sci. Comput. Michael Dellnitz, Eyke Hüllermeier, Marvin Lücke, Sina Ober-Blöbaum, Christian Offen, Sebastian Peitz, Karlson Pfannschmidt
2023	J	`jnl`	Identifying Copeland Winners in Dueling Bandits with Indifferences. CoRR Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
2023	—	`conf`	Identifying Trends in Feature Attributions During Training of Neural Networks. PKDD/ECML Workshops (2) Elena Terzieva, Maximilian Muschalik, Paul Hofman, Eyke Hüllermeier
2023	J	`jnl`	Incremental permutation feature importance (iPFI): towards online explanations on data streams. Mach. Learn. Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer
2023	J	`jnl`	Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty? CoRR Yusuf Sale, Michele Caprio, Eyke Hüllermeier
2023	A	`conf`	Is the volume of a credal set a good measure for epistemic uncertainty? UAI Yusuf Sale, Michele Caprio, Eyke Hüllermeier
2023	J	`jnl`	Iterative Deepening Hyperband. CoRR Jasmin Brandt, Marcel Wever, Dimitrios Iliadis, Viktor Bengs, Eyke Hüllermeier
2023	A*	`conf`	Koopman Kernel Regression. NeurIPS Petar Bevanda, Max Beier, Armin Lederer, Stefan Sosnowski, Eyke Hüllermeier, Sandra Hirche
2023	J	`jnl`	Koopman Kernel Regression. CoRR Petar Bevanda, Max Beier, Armin Lederer, Stefan Sosnowski, Eyke Hüllermeier, Sandra Hirche
2023	A*	`conf`	Memorization-Dilation: Modeling Neural Collapse Under Noise. ICLR Duc Anh Nguyen, Ron Levie, Julian Lienen, Eyke Hüllermeier, Gitta Kutyniok
2023	J	`jnl`	Mitigating Label Noise through Data Ambiguation. CoRR Julian Lienen, Eyke Hüllermeier
2023	J	`jnl`	Multi-armed bandits with censored consumption of resources. Mach. Learn. Viktor Bengs, Eyke Hüllermeier
2023	B	`conf`	On Feature Removal for Explainability in Dynamic Environments. ESANN Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer
2023	A*	`conf`	On Second-Order Scoring Rules for Epistemic Uncertainty Quantification. ICML Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2023	J	`jnl`	On Second-Order Scoring Rules for Epistemic Uncertainty Quantification. CoRR Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2023	A	`conf`	On the Calibration of Probabilistic Classifier Sets. AISTATS Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman
2023	—	`conf`	On the Challenges and Practices of Reinforcement Learning from Real Human Feedback. PKDD/ECML Workshops (2) Timo Kaufmann, Sarah Ball, Jacob Beck, Eyke Hüllermeier, Frauke Kreuter
2023	J	`jnl`	Optimizing Data Shapley Interaction Calculation from O(2^n) to O(t n^2) for KNN models. CoRR Mohamed Karim Belaid, Dorra El Mekki, Maximilian Rabus, Eyke Hüllermeier
2023	B	`conf`	Probabilistic Scoring Lists for Interpretable Machine Learning. DS Jonas Hanselle, Johannes Fürnkranz, Eyke Hüllermeier
2023	J	`jnl`	Probabilistic Self-supervised Learning via Scoring Rules Minimization. CoRR Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei
2023	C	`conf`	Property-Driven Black-Box Testing of Numeric Functions. Software Engineering Arnab Sharma, Vitalik Melnikov, Eyke Hüllermeier, Heike Wehrheim
2023	A	`conf`	Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures? UAI Lisa Wimmer, Yusuf Sale, Paul Hofman, Bernd Bischl, Eyke Hüllermeier
2023	—	`conf`	Rectifying Bias in Ordinal Observational Data Using Unimodal Label Smoothing. ECML/PKDD (6) Stefan Haas, Eyke Hüllermeier
2023	A*	`conf`	SHAP-IQ: Unified Approximation of any-order Shapley Interactions. NeurIPS Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer
2023	J	`jnl`	SHAP-IQ: Unified Approximation of any-order Shapley Interactions. CoRR Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Hammer
2023	J	`jnl`	Second-Order Uncertainty Quantification: A Distance-Based Approach. CoRR Yusuf Sale, Viktor Bengs, Michele Caprio, Eyke Hüllermeier
2023	J	`jnl`	Towards Green Automated Machine Learning: Status Quo and Future Directions. J. Artif. Intell. Res. Tanja Tornede, Alexander Tornede, Jonas Hanselle, Felix Mohr, Marcel Wever, Eyke Hüllermeier
2023	J	`jnl`	UNGOML: Automated Classification of unsafe Usages in Go. CoRR Anna-Katharina Wickert, Clemens Damke, Lars Baumgärtner, Eyke Hüllermeier, Mira Mezini
2023	A	`conf`	UnGoML: Automated Classification of unsafe Usages in Go. MSR Anna-Katharina Wickert, Clemens Damke, Lars Baumgärtner, Eyke Hüllermeier, Mira Mezini
2023	J	`jnl`	Weighting by Tying: A New Approach to Weighted Rank Correlation. CoRR Sascha Henzgen, Eyke Hüllermeier
2023	—	`conf`	iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. xAI (1) Maximilian Muschalik, Fabian Fumagalli, Rohit Jagtani, Barbara Hammer, Eyke Hüllermeier
2023	J	`jnl`	iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. CoRR Maximilian Muschalik, Fabian Fumagalli, Rohit Jagtani, Barbara Hammer, Eyke Hüllermeier
2023	—	`conf`	iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. ECML/PKDD (3) Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2023	J	`jnl`	iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. CoRR Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2022	—	`conf`	A Prescriptive Machine Learning Approach for Assessing Goodwill in the Automotive Domain. ECML/PKDD (6) Stefan Haas, Eyke Hüllermeier
2022	J	`jnl`	A Survey of Methods for Automated Algorithm Configuration. CoRR Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2022	J	`jnl`	A Survey of Methods for Automated Algorithm Configuration. J. Artif. Intell. Res. Elias Schede, Jasmin Brandt, Alexander Tornede, Marcel Wever, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2022	J	`jnl`	A flexible class of dependence-aware multi-label loss functions. Mach. Learn. Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp
2022	J	`jnl`	AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. CoRR Jasmin Brandt, Elias Schede, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier, Kevin Tierney
2022	B	`ed.`	Advances in Intelligent Data Analysis XX - 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20-22, 2022, Proceedings IDA Tassadit Bouadi, Élisa Fromont, Eyke Hüllermeier
2022	J	`jnl`	Agnostic Explanation of Model Change based on Feature Importance. Künstliche Intell. Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier
2022	—	`conf`	Automated Information Leakage Detection: A New Method Combining Machine Learning and Hypothesis Testing with an Application to Side-channel Detection in Cryptographic Protocols. ICAART (2) Pritha Gupta, Arunselvan Ramaswamy, Jan Peter Drees, Eyke Hüllermeier, Claudia Priesterjahn, Tibor Jager
2022	J	`jnl`	Conformal Credal Self-Supervised Learning. CoRR Julian Lienen, Caglar Demir, Eyke Hüllermeier
2022	J	`jnl`	Conformal Prediction Intervals for Remaining Useful Lifetime Estimation. CoRR Alireza Javanmardi, Eyke Hüllermeier
2022	J	`jnl`	Deep Q-Learning: Theoretical Insights From an Asymptotic Analysis. IEEE Trans. Artif. Intell. Arunselvan Ramaswamy, Eyke Hüllermeier
2022	J	`jnl`	Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark. CoRR Mohamed Karim Belaid, Eyke Hüllermeier, Maximilian Rabus, Ralf Krestel
2022	A*	`conf`	Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. NeurIPS Jasmin Brandt, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier
2022	J	`jnl`	Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. CoRR Jasmin Brandt, Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier
2022	J	`jnl`	How to measure uncertainty in uncertainty sampling for active learning. Mach. Learn. Vu-Linh Nguyen, Mohammad Hossein Shaker, Eyke Hüllermeier
2022	J	`jnl`	Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams. CoRR Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer
2022	J	`jnl`	Learning context-dependent choice functions. Int. J. Approx. Reason. Karlson Pfannschmidt, Pritha Gupta, Björn Haddenhorst, Eyke Hüllermeier
2022	—	`conf`	Levelwise Data Disambiguation by Cautious Superset Classification. SUM Julian Rodemann, Dominik Kreiss, Eyke Hüllermeier, Thomas Augustin
2022	A*	`conf`	Machine Learning for Online Algorithm Selection under Censored Feedback. AAAI Alexander Tornede, Viktor Bengs, Eyke Hüllermeier
2022	J	`jnl`	Memorization-Dilation: Modeling Neural Collapse Under Noise. CoRR Duc Anh Nguyen, Ron Levie, Julian Lienen, Gitta Kutyniok, Eyke Hüllermeier
2022	J	`jnl`	Non-Stationary Dueling Bandits. CoRR Patrick Kolpaczki, Viktor Bengs, Eyke Hüllermeier
2022	J	`jnl`	On Calibration of Ensemble-Based Credal Predictors. CoRR Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman
2022	J	`jnl`	On the Difficulty of Epistemic Uncertainty Quantification in Machine Learning: The Case of Direct Uncertainty Estimation through Loss Minimisation. CoRR Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2022	A*	`conf`	Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation. NeurIPS Viktor Bengs, Eyke Hüllermeier, Willem Waegeman
2022	—	`conf`	Property-Driven Testing of Black-Box Functions. FormaliSE@ICSE Arnab Sharma, Vitalik Melnikov, Eyke Hüllermeier, Heike Wehrheim
2022	A	`conf`	Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison. UAI Eyke Hüllermeier, Sébastien Destercke, Mohammad Hossein Shaker
2022	J	`jnl`	Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures? CoRR Eyke Hüllermeier
2022	—	`conf`	Representation and quantification of uncertainty in machine learning. LFA Eyke Hüllermeier
2022	—	`conf`	Scikit-Weak: A Python Library for Weakly Supervised Machine Learning. IJCRS Andrea Campagner, Julian Lienen, Eyke Hüllermeier, Davide Ciucci
2022	A	`conf`	Set-valued prediction in hierarchical classification with constrained representation complexity. UAI Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczynski, Willem Waegeman
2022	J	`jnl`	Set-valued prediction in hierarchical classification with constrained representation complexity. CoRR Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczynski, Willem Waegeman
2022	A*	`conf`	Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models. ICML Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
2022	J	`jnl`	Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models. CoRR Viktor Bengs, Aadirupa Saha, Eyke Hüllermeier
2022	—	`conf`	iART - Eine Suchmaschine zur Unterstützung von bildorientierten Forschungsprozessen. DHd Stefanie Schneider, Matthias Springstein, Javad Rahnama, Hubertus Kohle, Ralph Ewerth, Eyke Hüllermeier
2021	J	`jnl`	Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods. Mach. Learn. Eyke Hüllermeier, Willem Waegeman
2021	—	`conf`	Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. PAKDD (1) Jonas Hanselle, Alexander Tornede, Marcel Wever, Eyke Hüllermeier
2021	J	`jnl`	Algorithm Selection on a Meta Level. CoRR Alexander Tornede, Lukas Gehring, Tanja Tornede, Marcel Wever, Eyke Hüllermeier
2021	B	`conf`	Analogical Embedding for Analogy-Based Learning to Rank. IDA Mohsen Ahmadi Fahandar, Eyke Hüllermeier
2021	J	`jnl`	Annotation Uncertainty in the Context of Grammatical Change. CoRR Marie-Luis Merten, Marcel Wever, Michaela Geierhos, Doris Tophinke, Eyke Hüllermeier
2021	J	`jnl`	AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Trans. Pattern Anal. Mach. Intell. Marcel Wever, Alexander Tornede, Felix Mohr, Eyke Hüllermeier
2021	—	`conf`	Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs! AISec@CCS Jan Peter Drees, Pritha Gupta, Eyke Hüllermeier, Tibor Jager, Alexander Konze, Claudia Priesterjahn, Arunselvan Ramaswamy, Juraj Somorovsky
2021	J	`jnl`	Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs! IACR Cryptol. ePrint Arch. Jan Peter Drees, Pritha Gupta, Eyke Hüllermeier, Tibor Jager, Alexander Konze, Claudia Priesterjahn, Arunselvan Ramaswamy, Juraj Somorovsky
2021	J	`jnl`	Automated Machine Learning, Bounded Rationality, and Rational Metareasoning. CoRR Eyke Hüllermeier, Felix Mohr, Alexander Tornede, Marcel Wever
2021	A	`conf`	Coevolution of remaining useful lifetime estimation pipelines for automated predictive maintenance. GECCO Tanja Tornede, Alexander Tornede, Marcel Wever, Eyke Hüllermeier
2021	A*	`conf`	Credal Self-Supervised Learning. NeurIPS Julian Lienen, Eyke Hüllermeier
2021	J	`jnl`	Credal Self-Supervised Learning. CoRR Julian Lienen, Eyke Hüllermeier
2021	C	`conf`	Drift Detection in Text Data with Document Embeddings. IDEAL Robert Feldhans, Adrian Wilke, Stefan Heindorf, Mohammad Hossein Shaker, Barbara Hammer, Axel-Cyrille Ngonga Ngomo, Eyke Hüllermeier
2021	J	`jnl`	Efficient set-valued prediction in multi-class classification. Data Min. Knowl. Discov. Thomas Mortier, Marek Wydmuch, Krzysztof Dembczynski, Eyke Hüllermeier, Willem Waegeman
2021	J	`jnl`	Efficient time stepping for numerical integration using reinforcement learning. CoRR Michael Dellnitz, Eyke Hüllermeier, Marvin Lücke, Sina Ober-Blöbaum, Christian Offen, Sebastian Peitz, Karlson Pfannschmidt
2021	J	`jnl`	Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference. CoRR Mohammad Hossein Shaker, Eyke Hüllermeier
2021	J	`jnl`	Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Trans. Cogn. Dev. Syst. Katharina J. Rohlfing, Philipp Cimiano, Ingrid Scharlau, Tobias Matzner, Heike M. Buhl, Hendrik Buschmeier, Elena Esposito, Angela Grimminger, Barbara Hammer, Reinhold Häb-Umbach, Ilona Horwath, Eyke Hüllermeier, Friederike Kern, Stefan Kopp, Kirsten Thommes, Axel-Cyrille Ngonga Ngomo, Carsten Schulte, Henning Wachsmuth, Petra Wagner, Britta Wrede
2021	A*	`conf`	From Label Smoothing to Label Relaxation. AAAI Julian Lienen, Eyke Hüllermeier
2021	—	`conf`	Gradient-Based Label Binning in Multi-label Classification. ECML/PKDD (3) Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier
2021	J	`jnl`	Gradient-based Label Binning in Multi-label Classification. CoRR Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier
2021	A*	`conf`	Identification of the Generalized Condorcet Winner in Multi-dueling Bandits. NeurIPS Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier
2021	—	`conf`	Identifying Top-k Players in Cooperative Games via Shapley Bandits. LWDA Patrick Kolpaczki, Viktor Bengs, Eyke Hüllermeier
2021	J	`jnl`	Instance weighting through data imprecisiation. Int. J. Approx. Reason. Julian Lienen, Eyke Hüllermeier
2021	J	`jnl`	Machine Learning With the Sugeno Integral: The Case of Binary Classification. IEEE Trans. Fuzzy Syst. Sadegh Abbaszadeh, Eyke Hüllermeier
2021	J	`jnl`	Machine Learning for Online Algorithm Selection under Censored Feedback. CoRR Alexander Tornede, Viktor Bengs, Eyke Hüllermeier
2021	A*	`conf`	Monocular Depth Estimation via Listwise Ranking Using the Plackett-Luce Model. CVPR Julian Lienen, Eyke Hüllermeier, Ralph Ewerth, Nils Nommensen
2021	J	`jnl`	Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence. J. Artif. Intell. Res. Vu-Linh Nguyen, Eyke Hüllermeier
2021	J	`jnl`	On testing transitivity in online preference learning. Mach. Learn. Björn Haddenhorst, Viktor Bengs, Eyke Hüllermeier
2021	A*	`conf`	On the Identifiability of Hierarchical Decision Models. KR Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
2021	B	`conf`	Performance Prediction for Hardware-Software Configurations: A Case Study for Video Games. IDA Sven Peeters, Vitalik Melnikov, Eyke Hüllermeier
2021	J	`jnl`	Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. Felix Mohr, Marcel Wever, Alexander Tornede, Eyke Hüllermeier
2021	J	`jnl`	Preference-based Online Learning with Dueling Bandits: A Survey. J. Mach. Learn. Res. Viktor Bengs, Róbert Busa-Fekete, Adil El Mesaoudi-Paul, Eyke Hüllermeier
2021	J	`jnl`	Prescriptive Machine Learning for Automated Decision Making: Challenges and Opportunities. CoRR Eyke Hüllermeier
2021	B	`conf`	Ranking Structured Objects with Graph Neural Networks. DS Clemens Damke, Eyke Hüllermeier
2021	J	`jnl`	Ranking Structured Objects with Graph Neural Networks. CoRR Clemens Damke, Eyke Hüllermeier
2021	C	`conf`	Robust Regression for Monocular Depth Estimation. ACML Julian Lienen, Nils Nommensen, Ralph Ewerth, Eyke Hüllermeier
2021	J	`jnl`	Rough set-based feature selection for weakly labeled data. Int. J. Approx. Reason. Andrea Campagner, Davide Ciucci, Eyke Hüllermeier
2021	J	`jnl`	Safe Bayesian Optimization for Data-Driven Power Electronics Control Design in Microgrids: From Simulations to Real-World Experiments. IEEE Access Daniel Weber, Stefan Heid, Henrik Bode, Jarren H. Lange, Eyke Hüllermeier, Oliver Wallscheid
2021	A*	`conf`	Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model. AAAI Felix Mohr, Viktor Bengs, Eyke Hüllermeier
2021	J	`jnl`	TSK-Streams: learning TSK fuzzy systems for regression on data streams. Data Min. Knowl. Discov. Ammar Shaker, Eyke Hüllermeier
2021	A	`conf`	Testification of Condorcet Winners in dueling bandits. UAI Björn Haddenhorst, Viktor Bengs, Jasmin Brandt, Eyke Hüllermeier
2021	J	`jnl`	Towards Green Automated Machine Learning: Status Quo and Future Directions. CoRR Tanja Tornede, Alexander Tornede, Jonas Hanselle, Marcel Wever, Felix Mohr, Eyke Hüllermeier
2021	A*	`conf`	iART: A Search Engine for Art-Historical Images to Support Research in the Humanities. ACM Multimedia Matthias Springstein, Stefanie Schneider, Javad Rahnama, Eyke Hüllermeier, Hubertus Kohle, Ralph Ewerth
2021	J	`jnl`	iART: A Search Engine for Art-Historical Images to Support Research in the Humanities. CoRR Matthias Springstein, Stefanie Schneider, Javad Rahnama, Eyke Hüllermeier, Hubertus Kohle, Ralph Ewerth
2020	J	`jnl`	A Flexible Class of Dependence-aware Multi-Label Loss Functions. CoRR Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp
2020	B	`conf`	A Neural Network-Based Driver Gaze Classification System with Vehicle Signals. IJCNN Simone Dari, Nikolay Kadrileev, Eyke Hüllermeier
2020	C	`conf`	A Novel Higher-order Weisfeiler-Lehman Graph Convolution. ACML Clemens Damke, Vitalik Melnikov, Eyke Hüllermeier
2020	J	`jnl`	A Novel Higher-order Weisfeiler-Lehman Graph Convolution. CoRR Clemens Damke, Vitalik Melnikov, Eyke Hüllermeier
2020	B	`conf`	Aleatoric and Epistemic Uncertainty with Random Forests. IDA Mohammad Hossein Shaker, Eyke Hüllermeier
2020	J	`jnl`	Aleatoric and Epistemic Uncertainty with Random Forests. CoRR Mohammad Hossein Shaker, Eyke Hüllermeier
2020	J	`jnl`	Algorithm selection for software validation based on graph kernels. Autom. Softw. Eng. Cedric Richter, Eyke Hüllermeier, Marie-Christine Jakobs, Heike Wehrheim
2020	—	`conf`	AutoML for Predictive Maintenance: One Tool to RUL Them All. IoT Streams/ITEM@PKDD/ECML Tanja Tornede, Alexander Tornede, Marcel Wever, Felix Mohr, Eyke Hüllermeier
2020	J	`jnl`	Beyond Adaptation: Understanding Distributional Changes (Dagstuhl Seminar 20372). Dagstuhl Reports Georg Krempl, Vera Hofer, Geoffrey I. Webb, Eyke Hüllermeier
2020	Misc	`conf`	Conformal Rule-Based Multi-label Classification. KI Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía
2020	J	`jnl`	Conformal Rule-Based Multi-label Classification. CoRR Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía
2020	J	`jnl`	Extreme Algorithm Selection With Dyadic Feature Representation. CoRR Alexander Tornede, Marcel Wever, Eyke Hüllermeier
2020	B	`conf`	Extreme Algorithm Selection with Dyadic Feature Representation. DS Alexander Tornede, Marcel Wever, Eyke Hüllermeier
2020	—	`conf`	Feature Reduction in Superset Learning Using Rough Sets and Evidence Theory. IPMU (1) Andrea Campagner, Davide Ciucci, Eyke Hüllermeier
2020	J	`jnl`	Generalized transitivity: A systematic comparison of concepts with an application to preferences in the Babington Smith model. Int. J. Approx. Reason. Björn Haddenhorst, Eyke Hüllermeier, Martin Kolb
2020	—	`conf`	How to Measure Uncertainty in Uncertainty Sampling for Active Learning. IAL@PKDD/ECML Eyke Hüllermeier
2020	Misc	`conf`	Hybrid Ranking and Regression for Algorithm Selection. KI Jonas Hanselle, Alexander Tornede, Marcel Wever, Eyke Hüllermeier
2020	J	`jnl`	Introduction to the special issue of the ECML PKDD 2020 journal track. Data Min. Knowl. Discov. Ira Assent, Carlotta Domeniconi, Aristides Gionis, Eyke Hüllermeier
2020	J	`jnl`	Introduction to the special issue of the ECML PKDD 2020 journal track. Mach. Learn. Ira Assent, Carlotta Domeniconi, Aristides Gionis, Eyke Hüllermeier
2020	Misc	`conf`	Learning Choice Functions via Pareto-Embeddings. KI Karlson Pfannschmidt, Eyke Hüllermeier
2020	J	`jnl`	Learning Choice Functions via Pareto-Embeddings. CoRR Karlson Pfannschmidt, Eyke Hüllermeier
2020	—	`conf`	Learning Gradient Boosted Multi-label Classification Rules. ECML/PKDD (3) Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
2020	J	`jnl`	Learning Gradient Boosted Multi-label Classification Rules. CoRR Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen, Eyke Hüllermeier
2020	J	`jnl`	Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning. CoRR Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Michael Rapp
2020	—	`conf`	Learning Tversky Similarity. IPMU (2) Javad Rahnama, Eyke Hüllermeier
2020	J	`jnl`	Learning Tversky Similarity. CoRR Javad Rahnama, Eyke Hüllermeier
2020	B	`conf`	LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-label Classification. IDA Marcel Wever, Alexander Tornede, Felix Mohr, Eyke Hüllermeier
2020	J	`jnl`	Machine Learning with the Sugeno Integral: The Case of Binary Classification. CoRR Sadegh Abbaszadeh, Eyke Hüllermeier
2020	J	`jnl`	Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model. CoRR Julian Lienen, Eyke Hüllermeier
2020	J	`jnl`	Multi-Armed Bandits with Censored Consumption of Resources. CoRR Viktor Bengs, Eyke Hüllermeier
2020	J	`jnl`	Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches. IEEE Trans. Cogn. Dev. Syst. Katharina J. Rohlfing, Giuseppe Leonardi, Iris Nomikou, Joanna Raczaszek-Leonardi, Eyke Hüllermeier
2020	A*	`conf`	Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals. IJCAI Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
2020	J	`jnl`	OMG: A Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control. J. Open Source Softw. Stefan Heid, Daniel Weber, Henrik Bode, Eyke Hüllermeier, Oliver Wallscheid
2020	B	`conf`	On Aggregation in Ensembles of Multilabel Classifiers. DS Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2020	J	`jnl`	On Aggregation in Ensembles of Multilabel Classifiers. CoRR Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz
2020	J	`jnl`	Online Preselection with Context Information under the Plackett-Luce Model. CoRR Adil El Mesaoudi-Paul, Viktor Bengs, Eyke Hüllermeier
2020	—	`conf`	Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. LION Adil El Mesaoudi-Paul, Dimitri Weiß, Viktor Bengs, Eyke Hüllermeier, Kevin Tierney
2020	A*	`conf`	Preselection Bandits. ICML Viktor Bengs, Eyke Hüllermeier
2020	A*	`conf`	Reliable Multilabel Classification: Prediction with Partial Abstention. AAAI Vu-Linh Nguyen, Eyke Hüllermeier
2020	J	`jnl`	Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction. CoRR Stefan Heid, Marcel Wever, Eyke Hüllermeier
2020	B	`conf`	Rule-Based Multi-label Classification: Challenges and Opportunities. RuleML+RR Eyke Hüllermeier, Johannes Fürnkranz, Eneldo Loza Mencía, Vu-Linh Nguyen, Michael Rapp
2020	C	`conf`	Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. ACML Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, Eyke Hüllermeier
2020	J	`jnl`	Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. CoRR Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, Eyke Hüllermeier
2020	—	`conf`	The Dissimilar in the Similar. An Attribute-guided Approach to the Subject-specific Classification of Art-historical Objects. GI-Jahrestagung Stefanie Schneider, Matthias Springstein, Javad Rahnama, Eyke Hüllermeier, Ralph Ewerth, Hubertus Kohle
2020	B	`conf`	Towards Analogy-Based Explanations in Machine Learning. MDAI Eyke Hüllermeier
2020	J	`jnl`	Towards Analogy-Based Explanations in Machine Learning. CoRR Eyke Hüllermeier
2020	J	`jnl`	Towards Meta-Algorithm Selection. CoRR Alexander Tornede, Marcel Wever, Eyke Hüllermeier
2020	J	`jnl`	Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control. CoRR Henrik Bode, Stefan Heid, Daniel Weber, Eyke Hüllermeier, Oliver Wallscheid
2019	—	`conf`	A Reduction of Label Ranking to Multiclass Classification. ECML/PKDD (3) Klaus Brinker, Eyke Hüllermeier
2019	J	`jnl`	Aleatoric and Epistemic Uncertainty in Machine Learning: A Tutorial Introduction. CoRR Eyke Hüllermeier, Willem Waegeman
2019	Misc	`conf`	Analogy-Based Preference Learning with Kernels. KI Mohsen Ahmadi Fahandar, Eyke Hüllermeier
2019	J	`jnl`	Analogy-Based Preference Learning with Kernels. CoRR Mohsen Ahmadi Fahandar, Eyke Hüllermeier
2019	J	`jnl`	Choice Functions Generated by Mallows and Plackett-Luce Relations. New Math. Nat. Comput. Vidal Kamdem Tagne, Siméon Fotso, Louis Aimé Fono, Eyke Hüllermeier
2019	J	`jnl`	Efficient Algorithms for Set-Valued Prediction in Multi-Class Classification. CoRR Thomas Mortier, Marek Wydmuch, Eyke Hüllermeier, Krzysztof Dembczynski, Willem Waegeman
2019	B	`conf`	Epistemic Uncertainty Sampling. DS Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier
2019	J	`jnl`	Epistemic Uncertainty Sampling. CoRR Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier
2019	B	`conf`	Feature Selection for Analogy-Based Learning to Rank. DS Mohsen Ahmadi Fahandar, Eyke Hüllermeier
2019	—	`conf`	From Automated to On-The-Fly Machine Learning. GI-Jahrestagung Felix Mohr, Marcel Wever, Alexander Tornede, Eyke Hüllermeier
2019	J	`jnl`	Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning. IEEE Comput. Intell. Mag. Inés Couso, Christian Borgelt, Eyke Hüllermeier, Rudolf Kruse
2019	J	`jnl`	Learning Choice Functions. CoRR Karlson Pfannschmidt, Pritha Gupta, Eyke Hüllermeier
2019	—	`conf`	Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants. SUM Eyke Hüllermeier, Sébastien Destercke, Inés Couso
2019	C	`conf`	Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA. ACML Vitalik Melnikov, Eyke Hüllermeier
2019	J	`jnl`	Mining Rank Data. ACM Trans. Knowl. Discov. Data Sascha Henzgen, Eyke Hüllermeier
2019	J	`jnl`	Multi-target prediction: a unifying view on problems and methods. Data Min. Knowl. Discov. Willem Waegeman, Krzysztof Dembczynski, Eyke Hüllermeier
2019	J	`jnl`	Preselection Bandits under the Plackett-Luce Model. CoRR Viktor Bengs, Eyke Hüllermeier
2019	J	`jnl`	Rectifying Classifier Chains for Multi-Label Classification. CoRR Robin Senge, Juan José del Coz, Eyke Hüllermeier
2019	J	`jnl`	Reliable Multi-label Classification: Prediction with Partial Abstention. CoRR Vu-Linh Nguyen, Eyke Hüllermeier
2019	—	`conf`	Set-Valued Prediction in Multi-Class Classification. BNAIC/BENELEARN Thomas Mortier, Marek Wydmuch, Krzysztof Dembczynski, Eyke Hüllermeier, Willem Waegeman
2019	J	`jnl`	TSK-Streams: Learning TSK Fuzzy Systems on Data Streams. CoRR Ammar Shaker, Eyke Hüllermeier
2018	—	`conf`	(WIP) Towards the Automated Composition of Machine Learning Services. SCC Felix Mohr, Marcel Wever, Eyke Hüllermeier, Amin Faez
2018	J	`jnl`	Automated Machine Learning Service Composition. CoRR Felix Mohr, Marcel Wever, Eyke Hüllermeier
2018	J	`jnl`	Automated Multi-Label Classification based on ML-Plan. CoRR Marcel Wever, Felix Mohr, Eyke Hüllermeier
2018	J	`jnl`	Deep architectures for learning context-dependent ranking functions. CoRR Karlson Pfannschmidt, Pritha Gupta, Eyke Hüllermeier
2018	J	`jnl`	Dyad ranking using Plackett-Luce models based on joint feature representations. Mach. Learn. Dirk Schäfer, Eyke Hüllermeier
2018	A	`conf`	Ensembles of evolved nested dichotomies for classification. GECCO Marcel Wever, Felix Mohr, Eyke Hüllermeier
2018	J	`jnl`	Learning Interpretable Rules for Multi-label Classification. CoRR Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier, Michael Rapp
2018	A*	`conf`	Learning to Rank Based on Analogical Reasoning. AAAI Mohsen Ahmadi Fahandar, Eyke Hüllermeier
2018	J	`jnl`	ML-Plan: Automated machine learning via hierarchical planning. Mach. Learn. Felix Mohr, Marcel Wever, Eyke Hüllermeier
2018	J	`jnl`	Mining Rank Data. CoRR Sascha Henzgen, Eyke Hüllermeier
2018	J	`jnl`	Multi-Target Prediction: A Unifying View on Problems and Methods. CoRR Willem Waegeman, Krzysztof Dembczynski, Eyke Hüllermeier
2018	J	`jnl`	On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis. Mach. Learn. Vitalik Melnikov, Eyke Hüllermeier
2018	—	`conf`	On-the-Fly Service Construction with Prototypes. SCC Felix Mohr, Marcel Wever, Eyke Hüllermeier
2018	B	`conf`	Preference-Based Reinforcement Learning Using Dyad Ranking. DS Dirk Schäfer, Eyke Hüllermeier
2018	J	`jnl`	Preference-based Online Learning with Dueling Bandits: A Survey. CoRR Róbert Busa-Fekete, Eyke Hüllermeier, Adil El Mesaoudi-Paul
2018	A*	`conf`	Ranking Distributions based on Noisy Sorting. ICML Adil El Mesaoudi-Paul, Eyke Hüllermeier, Róbert Busa-Fekete
2018	B	`conf`	Reduction Stumps for Multi-class Classification. IDA Felix Mohr, Marcel Wever, Eyke Hüllermeier
2018	A*	`conf`	Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. IJCAI Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson, Eyke Hüllermeier
2018	J	`jnl`	Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). Dagstuhl Manifestos 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
2017	—	`conf`	Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German. LaTeCH@ACL Nina Seemann, Marie-Luis Merten, Michaela Geierhos, Doris Tophinke, Eyke Hüllermeier
2017	A	`conf`	Estimating relative depth in single images via rankboost. ICME Ralph Ewerth, Matthias Springstein, Eric Müller, Alexander Balz, Jan Gehlhaar, Tolga Naziyok, Krzysztof Dembczynski, Eyke Hüllermeier
2017	J	`jnl`	From knowledge-based to data-driven modeling of fuzzy rule-based systems: A critical reflection. CoRR Eyke Hüllermeier
2017	J	`jnl`	Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic. IEEE Trans. Software Eng. Marie Christin Platenius, Ammar Shaker, Matthias Becker, Eyke Hüllermeier, Wilhelm Schäfer
2017	C	`conf`	Keynote 4: "Large-scale machine learning and extreme classification". CoDIT Eyke Hüllermeier
2017	—	`conf`	Learning TSK Fuzzy Rules from Data Streams. ECML/PKDD (2) Ammar Shaker, Waleri Heldt, Eyke Hüllermeier
2017	J	`jnl`	Learning to Rank based on Analogical Reasoning. CoRR Mohsen Ahmadi Fahandar, Eyke Hüllermeier
2017	J	`jnl`	Lexicographic preferences for predictive modeling of human decision making: A new machine learning method with an application in accounting. Eur. J. Oper. Res. Michael Bräuning, Eyke Hüllermeier, Tobias Keller, Martin Glaum
2017	—	`conf`	Maximum Likelihood Estimation and Coarse Data. SUM Inés Couso, Didier Dubois, Eyke Hüllermeier
2017	Misc	`conf`	Planning with Independent Task Networks. KI Felix Mohr, Theo Lettmann, Eyke Hüllermeier
2017	J	`jnl`	Predicting Rankings of Software Verification Competitions. CoRR Mike Czech, Eyke Hüllermeier, Marie-Christine Jakobs, Heike Wehrheim
2017	—	`conf`	Predicting rankings of software verification tools. SWAN@ESEC/SIGSOFT FSE Mike Czech, Eyke Hüllermeier, Marie-Christine Jakobs, Heike Wehrheim
2017	—	`ch.`	Preference Learning. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz, Eyke Hüllermeier
2017	—	`ch.`	Rank Correlation. Encyclopedia of Machine Learning and Data Mining Johannes Fürnkranz, Eyke Hüllermeier
2017	J	`jnl`	Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). CoRR 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
2017	A*	`conf`	Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening. ICML Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso
2017	J	`jnl`	Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening. CoRR Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso
2016	J	`jnl`	CavSimBase: A Database for Large Scale Comparison of Protein Binding Sites. IEEE Trans. Knowl. Data Eng. Matthias Leinweber, Thomas Fober, Marc Strickert, Lars Baumgärtner, Gerhard Klebe, Bernd Freisleben, Eyke Hüllermeier
2016	—	`conf`	Consistency of Probabilistic Classifier Trees. ECML/PKDD (2) Krzysztof Dembczynski, Wojciech Kotlowski, Willem Waegeman, Róbert Busa-Fekete, Eyke Hüllermeier
2016	A	`ed.`	ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands - Including Prestigious Applications of Artificial Intelligence (PAIS 2016) ECAI Gal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum, Frank van Harmelen
2016	—	`conf`	Evaluating Tests in Medical Diagnosis: Combining Machine Learning with Game-Theoretical Concepts. IPMU (1) Karlson Pfannschmidt, Eyke Hüllermeier, Susanne Held, Reto Neiger
2016	J	`jnl`	Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification. BioData Min. Mona Riemenschneider, Robin Senge, Ursula Neumann, Eyke Hüllermeier, Dominik Heider
2016	A*	`conf`	Extreme F-measure Maximization using Sparse Probability Estimates. ICML Kalina Jasinska, Krzysztof Dembczynski, Róbert Busa-Fekete, Karlson Pfannschmidt, Timo Klerx, Eyke Hüllermeier
2016	—	`conf`	Learning to Aggregate Using Uninorms. ECML/PKDD (2) Vitalik Melnikov, Eyke Hüllermeier
2016	—	`conf`	Plackett-Luce Networks for Dyad Ranking. LWDA Dirk Schäfer, Eyke Hüllermeier
2016	C	`conf`	Predicting the Electricity Consumption of Buildings: An Improved CBR Approach. ICCBR Aulon Shabani, Adil Paul, Radu Platon, Eyke Hüllermeier
2016	J	`jnl`	Research Directions for Principles of Data Management (Abridged). SIGMOD Rec. 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	J	`jnl`	Special Issue on Discovery Science. Inf. Sci. Johannes Fürnkranz, Eyke Hüllermeier
2015	—	`conf`	A CBR Approach to the Angry Birds Game. ICCBR (Workshops) Adil Paul, Eyke Hüllermeier
2015	C	`conf`	Case Base Maintenance in Preference-Based CBR. ICCBR Amira Abdel-Aziz, Eyke Hüllermeier
2015	C	`ed.`	Case-Based Reasoning Research and Development - 23rd International Conference, ICCBR 2015, Frankfurt am Main, Germany, September 28-30, 2015, Proceedings ICCBR Eyke Hüllermeier, Mirjam Minor
2015	J	`jnl`	Does machine learning need fuzzy logic? Fuzzy Sets Syst. Eyke Hüllermeier
2015	—	`conf`	Dyad Ranking Using A Bilinear Plackett-Luce Model. ECML/PKDD (2) Dirk Schäfer, Eyke Hüllermeier
2015	J	`jnl`	Editorial. Fuzzy Sets Syst. Bernard De Baets, Didier Dubois, Eyke Hüllermeier
2015	J	`jnl`	Fast Fuzzy Pattern Tree Learning for Classification. IEEE Trans. Fuzzy Syst. Robin Senge, Eyke Hüllermeier
2015	J	`jnl`	From knowledge-based to data-driven fuzzy modeling - Development, criticism, and alternative directions. Inform. Spektrum Eyke Hüllermeier
2015	—	`conf`	Online F-Measure Optimization. NIPS Róbert Busa-Fekete, Balázs Szörényi, Krzysztof Dembczynski, Eyke Hüllermeier
2015	—	`conf`	Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach. NIPS Balázs Szörényi, Róbert Busa-Fekete, Adil Paul, Eyke Hüllermeier
2015	J	`jnl`	Overlap Indices: Construction of and Application to Interpolative Fuzzy Systems. IEEE Trans. Fuzzy Syst. Santiago García-Jiménez, Humberto Bustince, Eyke Hüllermeier, Radko Mesiar, Nikhil R. Pal, Ana Pradera
2015	—	`conf`	Preference-Based Meta-Learning using Dyad Ranking: Recommending Algorithms in Cold-Start Situations. MetaSel@PKDD/ECML Dirk Schäfer, Eyke Hüllermeier
2015	A*	`conf`	Qualitative Multi-Armed Bandits: A Quantile-Based Approach. ICML Balázs Szörényi, Róbert Busa-Fekete, Paul Weng, Eyke Hüllermeier
2015	J	`jnl`	Recovery analysis for adaptive learning from non-stationary data streams: Experimental design and case study. Neurocomputing Ammar Shaker, Eyke Hüllermeier
2015	—	`conf`	Superset Learning Based on Generalized Loss Minimization. ECML/PKDD (2) Eyke Hüllermeier, Weiwei Cheng
2015	—	`conf`	Weighted Rank Correlation: A Flexible Approach Based on Fuzzy Order Relations. ECML/PKDD (2) Sascha Henzgen, Eyke Hüllermeier
2014	B	`conf`	A Survey of Preference-Based Online Learning with Bandit Algorithms. ALT Róbert Busa-Fekete, Eyke Hüllermeier
2014	J	`jnl`	Ausgewählte Beiträge des GMA-Fachausschusses 5.14 "Computational Intelligence". Autom. Frank Hoffmann, Eyke Hüllermeier, Andreas Kroll
2014	J	`jnl`	Correlation-based embedding of pairwise score data. Neurocomputing Marc Strickert, Kerstin Bunte, Frank-Michael Schleif, Eyke Hüllermeier
2014	J	`jnl`	Dependent binary relevance models for multi-label classification. Pattern Recognit. Elena Montañés, Robin Senge, José Barranquero, José Ramón Quevedo, Juan José del Coz, Eyke Hüllermeier
2014	—	`conf`	Dyad Ranking Using a Bilinear Plackett-Luce Model. LWA Dirk Schäfer, Eyke Hüllermeier
2014	J	`jnl`	Extended Graph-Based Models for Enhanced Similarity Search in Cavbase. IEEE ACM Trans. Comput. Biol. Bioinform. Timo Krotzky, Thomas Fober, Eyke Hüllermeier, Gerhard Klebe
2014	J	`jnl`	Guest Editors' introduction: special issue of the ECML/PKDD 2014 journal track. Mach. Learn. Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo
2014	J	`jnl`	Guest editors' introduction: special issue of the ECML/PKDD 2014 journal track. Data Min. Knowl. Discov. Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo
2014	J	`jnl`	Identification of Functionally Related Enzymes by Learning-to-Rank Methods. IEEE ACM Trans. Comput. Biol. Bioinform. Michiel Stock, Thomas Fober, Eyke Hüllermeier, Serghei Glinca, Gerhard Klebe, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman
2014	J	`jnl`	Identification of functionally related enzymes by learning-to-rank methods. CoRR Michiel Stock, Thomas Fober, Eyke Hüllermeier, Serghei Glinca, Gerhard Klebe, Tapio Pahikkala, Antti Airola, Bernard De Baets, Willem Waegeman
2014	C	`conf`	Learning Solution Similarity in Preference-Based CBR. ICCBR Amira Abdel-Aziz, Marc Strickert, Eyke Hüllermeier
2014	J	`jnl`	Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. Int. J. Approx. Reason. Eyke Hüllermeier
2014	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part I ECML/PKDD (1) Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo
2014	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part II ECML/PKDD (2) Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo
2014	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part III ECML/PKDD (3) Toon Calders, Floriana Esposito, Eyke Hüllermeier, Rosa Meo
2014	B	`conf`	Mining Rank Data. Discovery Science Sascha Henzgen, Eyke Hüllermeier
2014	J	`jnl`	On the bayes-optimality of F-measure maximizers. J. Mach. Learn. Res. Willem Waegeman, Krzysztof Dembczynski, Arkadiusz Jachnik, Weiwei Cheng, Eyke Hüllermeier
2014	J	`jnl`	Open challenges for data stream mining research. SIGKDD Explor. Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski
2014	A*	`conf`	PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences. AAAI Róbert Busa-Fekete, Balázs Szörényi, Eyke Hüllermeier
2014	J	`jnl`	Preference Learning (Dagstuhl Seminar 14101). Dagstuhl Reports Johannes Fürnkranz, Eyke Hüllermeier, Cynthia Rudin, Roman Slowinski, Scott Sanner
2014	A*	`conf`	Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows. ICML Róbert Busa-Fekete, Eyke Hüllermeier, Balázs Szörényi
2014	J	`jnl`	Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm. Mach. Learn. Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier
2014	J	`jnl`	Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances. J. Bioinform. Comput. Biol. Marco Mernberger, Daniel Moog, Simone Stork, Stefan Zauner, Uwe G. Maier, Eyke Hüllermeier
2014	J	`jnl`	Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization". Int. J. Approx. Reason. Eyke Hüllermeier
2014	J	`jnl`	Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty. Inf. Sci. Robin Senge, Stefan Bösner, Krzysztof Dembczynski, Jörg Haasenritter, Oliver Hirsch, Norbert Donner-Banzhoff, Eyke Hüllermeier
2014	J	`jnl`	Survival analysis on data streams: Analyzing temporal events in dynamically changing environments. Int. J. Appl. Math. Comput. Sci. Ammar Shaker, Eyke Hüllermeier
2014	B	`conf`	The Choquet kernel for monotone data. ESANN Ali Fallah Tehrani, Marc Strickert, Eyke Hüllermeier
2014	J	`jnl`	Visualization of evolving fuzzy rule-based systems. Evol. Syst. Sascha Henzgen, Marc Strickert, Eyke Hüllermeier
2013	B	`ed.`	Discovery Science - 16th International Conference, DS 2013, Singapore, October 6-9, 2013. Proceedings Discovery Science Johannes Fürnkranz, Eyke Hüllermeier, Tomoyuki Higuchi
2013	J	`jnl`	Editorial: Preference learning and ranking. Mach. Learn. Eyke Hüllermeier, Johannes Fürnkranz
2013	J	`jnl`	Evolving fuzzy pattern trees for binary classification on data streams. Inf. Sci. Ammar Shaker, Robin Senge, Eyke Hüllermeier
2013	J	`jnl`	Extended graph-based models for enhanced similarity retrieval in Cavbase. J. Cheminformatics Timo Krotzky, Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier
2013	—	`conf`	Fuzzy pattern trees as an alternative to rule-based fuzzy systems: Knowledge-driven, data-driven and hybrid modeling of color yield in polyester dyeing. IFSA/NAFIPS Maryam Nasiri, Thomas Fober, Robin Senge, Eyke Hüllermeier
2013	J	`jnl`	Graph-based methods for protein structure comparison. WIREs Data Mining Knowl. Discov. Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier
2013	—	`conf`	Labelwise versus Pairwise Decomposition in Label Ranking. LWA Weiwei Cheng, Sascha Henzgen, Eyke Hüllermeier
2013	C	`conf`	Learning from Imprecise and Fuzzy Data: on the Notion of Data Disambiguation. IJCCI Eyke Hüllermeier
2013	J	`jnl`	Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization CoRR Eyke Hüllermeier
2013	A*	`conf`	Learning to Rank Lexical Substitutions. EMNLP György Szarvas, Róbert Busa-Fekete, Eyke Hüllermeier
2013	—	`ch.`	Local Clique Merging: An Extension of the Maximum Common Subgraph Measure with Applications in Structural Bioinformatics. Algorithms from and for Nature and Life Thomas Fober, Gerhard Klebe, Eyke Hüllermeier
2013	J	`jnl`	Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistance prediction. Bioinform. Dominik Heider, Robin Senge, Weiwei Cheng, Eyke Hüllermeier
2013	—	`conf`	Neighbor Embedding by Soft Kendall Correlation. EuroVis (Short Papers) Marc Strickert, Eyke Hüllermeier
2013	J	`jnl`	On the Bayes-optimality of F-measure maximizers. CoRR Willem Waegeman, Krzysztof Dembczynski, Weiwei Cheng, Eyke Hüllermeier
2013	—	`conf`	Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization. ICML (3) Krzysztof Dembczynski, Arkadiusz Jachnik, Wojciech Kotlowski, Willem Waegeman, Eyke Hüllermeier
2013	—	`conf`	Ordinal Choquistic Regression. EUSFLAT Conf. Ali Fallah Tehrani, Eyke Hüllermeier
2013	C	`conf`	Preference-Based CBR: A Search-Based Problem Solving Framework. ICCBR Amira Abdel-Aziz, Weiwei Cheng, Marc Strickert, Eyke Hüllermeier
2013	A*	`conf`	Preference-Based CBR: General Ideas and Basic Principles. IJCAI Eyke Hüllermeier, Weiwei Cheng
2013	—	`conf`	Recovery Analysis for Adaptive Learning from Non-stationary Data Streams. CORES Ammar Shaker, Eyke Hüllermeier
2013	—	`conf`	Rectifying Classifier Chains for Multi-Label Classification. LWA Robin Senge, Juan José del Coz, Eyke Hüllermeier
2013	—	`conf`	Rule Chains for Visualizing Evolving Fuzzy Rule-Based Systems. CORES Sascha Henzgen, Marc Strickert, Eyke Hüllermeier
2013	—	`conf`	Top-k Selection based on Adaptive Sampling of Noisy Preferences. ICML (3) Róbert Busa-Fekete, Balázs Szörényi, Weiwei Cheng, Paul Weng, Eyke Hüllermeier
2012	J	`jnl`	A WEKA Interface for fMRI Data. Neuroinformatics Martin Pyka, Alexander Balz, Andreas Jansen, Axel Krug, Eyke Hüllermeier
2012	J	`jnl`	A formal and empirical analysis of the fuzzy gamma rank correlation coefficient. Inf. Sci. M. Dolores Ruiz, Eyke Hüllermeier
2012	A	`conf`	An Analysis of Chaining in Multi-Label Classification. ECAI Krzysztof Dembczynski, Willem Waegeman, Eyke Hüllermeier
2012	J	`jnl`	Ausgewählte Beiträge des GMA-Fachausschusses 5.14 "Computational Intelligence". Autom. Frank Hoffmann, Eyke Hüllermeier, Andreas Kroll
2012	J	`jnl`	Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures. IEEE Trans. Fuzzy Syst. Eyke Hüllermeier, Maria Rifqi, Sascha Henzgen, Robin Senge
2012	A*	`conf`	Consistent Multilabel Ranking through Univariate Losses. ICML Krzysztof Dembczynski, Wojciech Kotlowski, Eyke Hüllermeier
2012	—	`conf`	F-Measure Maximization in Topical Classification. RSCTC Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier, Adrian Jaroszewicz, Willem Waegeman
2012	J	`jnl`	Fuzzy Pattern Trees: Ein alternativer Ansatz zur Fuzzy-Modellierung. Autom. Robin Senge, Thomas Fober, Maryam Nasiri, Eyke Hüllermeier
2012	—	`ch.`	Fuzzy Rules in Data Mining: From Fuzzy Associations to Gradual Dependencies. Combining Experimentation and Theory Eyke Hüllermeier
2012	—	`conf`	GPU-based Cloud computing for comparing the structure of protein binding sites. DEST Matthias Leinweber, Lars Baumgärtner, Marco Mernberger, Thomas Fober, Eyke Hüllermeier, Gerhard Klebe, Bernd Freisleben
2012	J	`jnl`	Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons. IEEE Trans. Fuzzy Syst. Humberto Bustince Sola, Miguel Pagola, Radko Mesiar, Eyke Hüllermeier, Francisco Herrera
2012	J	`jnl`	IBLStreams: a system for instance-based classification and regression on data streams. Evol. Syst. Ammar Shaker, Eyke Hüllermeier
2012	—	`conf`	Label Ranking with Partial Abstention based on Thresholded Probabilistic Models. NIPS Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman, Volkmar Welker
2012	J	`jnl`	Learning monotone nonlinear models using the Choquet integral. Mach. Learn. Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier
2012	J	`jnl`	On label dependence and loss minimization in multi-label classification. Mach. Learn. Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
2012	—	`conf`	On the Problem of Error Propagation in Classifier Chains for Multi-label Classification. GfKl Robin Senge, Juan José del Coz, Eyke Hüllermeier
2012	—	`conf`	On the VC-Dimension of the Choquet Integral. IPMU (1) Eyke Hüllermeier, Ali Fallah Tehrani
2012	J	`jnl`	Preference Learning Using the Choquet Integral: The Case of Multipartite Ranking. IEEE Trans. Fuzzy Syst. Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier
2012	J	`jnl`	Preference-based reinforcement learning: a formal framework and a policy iteration algorithm. Mach. Learn. Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park
2012	—	`conf`	Probability Estimation for Multi-class Classification Based on Label Ranking. ECML/PKDD (2) Weiwei Cheng, Eyke Hüllermeier
2012	—	`ed.`	Scalable Uncertainty Management - 6th International Conference, SUM 2012, Marburg, Germany, September 17-19, 2012. Proceedings SUM Eyke Hüllermeier, Sebastian Link, Thomas Fober, Bernhard Seeger
2011	—	`conf`	An Exact Algorithm for F-Measure Maximization. NIPS Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
2011	A*	`conf`	Bipartite Ranking through Minimization of Univariate Loss. ICML Wojciech Kotlowski, Krzysztof Dembczynski, Eyke Hüllermeier
2011	—	`conf`	Choquistic Regression: Generalizing Logistic Regression using the Choquet Integral. EUSFLAT Conf. Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier
2011	—	`conf`	Evolving Fuzzy Pattern Trees for Binary Classification on Data Streams. LWA Ammar Shaker, Robin Senge, Eyke Hüllermeier
2011	J	`jnl`	Fuzzy machine learning and data mining. WIREs Data Mining Knowl. Discov. Eyke Hüllermeier
2011	J	`jnl`	Fuzzy sets in machine learning and data mining. Appl. Soft Comput. Eyke Hüllermeier
2011	J	`jnl`	Label Ranking with Abstention: Predicting Partial Orders by Thresholding Probability Distributions (Extended Abstract) CoRR Weiwei Cheng, Eyke Hüllermeier
2011	—	`conf`	Learning Monotone Nonlinear Models Using the Choquet Integral. ECML/PKDD (3) Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier
2011	—	`conf`	Learning Monotone Nonlinear Models using the Choquet Integral. LWA Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier
2011	B	`conf`	Learning from Label Preferences. ALT Eyke Hüllermeier, Johannes Fürnkranz
2011	B	`conf`	Learning from Label Preferences. Discovery Science Eyke Hüllermeier, Johannes Fürnkranz
2011	—	`conf`	On-line Redundancy Elimination in Evolving Fuzzy Regression Models using a Fuzzy Inclusion Measure. EUSFLAT Conf. Edwin Lughofer, Eyke Hüllermeier
2011	C	`conf`	Preference-Based CBR: First Steps toward a Methodological Framework. ICCBR Eyke Hüllermeier, Patrice Schlegel
2011	—	`conf`	Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning. ECML/PKDD (1) Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park
2011	J	`jnl`	Preferences in AI: An overview. Artif. Intell. Carmel Domshlak, Eyke Hüllermeier, Souhila Kaci, Henri Prade
2011	J	`jnl`	SEGA: Semiglobal Graph Alignment for Structure-Based Protein Comparison. IEEE ACM Trans. Comput. Biol. Bioinform. Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier
2011	J	`jnl`	Superposition and Alignment of Labeled Point Clouds. IEEE ACM Trans. Comput. Biol. Bioinform. Thomas Fober, Serghei Glinca, Gerhard Klebe, Eyke Hüllermeier
2011	J	`jnl`	Top-Down Induction of Fuzzy Pattern Trees. IEEE Trans. Fuzzy Syst. Robin Senge, Eyke Hüllermeier
2010	—	`ch.`	An Analysis of the FURIA Algorithm for Fuzzy Rule Induction. Advances in Machine Learning I Jens Christian Hühn, Eyke Hüllermeier
2010	A*	`conf`	Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains. ICML Krzysztof Dembczynski, Weiwei Cheng, Eyke Hüllermeier
2010	J	`jnl`	Combining predictions in pairwise classification: An optimal adaptive voting strategy and its relation to weighted voting. Pattern Recognit. Eyke Hüllermeier, Stijn Vanderlooy
2010	C	`ed.`	Computational Intelligence for Knowledge-Based Systems Design, 13th International Conference on Information Processing and Management of Uncertainty, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings IPMU Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann
2010	—	`conf`	Efficient Similarity Retrieval of Protein Binding Sites based on Histogram Comparison. GCB Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier
2010	J	`jnl`	GARLig: A Fully Automated Tool for Subset Selection of Large Fragment Spaces via a Self-Adaptive Genetic Algorithm. J. Chem. Inf. Model. Patrick Pfeffer, Thomas Fober, Eyke Hüllermeier, Gerhard Klebe
2010	A*	`conf`	Graded Multilabel Classification: The Ordinal Case. ICML Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier
2010	—	`conf`	Graded Multilabel Classification: The Ordinal Case. LWA Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier
2010	—	`ed.`	Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications - 13th International Conference, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings, Part II IPMU (2) Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann
2010	—	`ed.`	Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods - 13th International Conference, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings, Part I IPMU (1) Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann
2010	A*	`conf`	Label Ranking Methods based on the Plackett-Luce Model. ICML Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier
2010	—	`conf`	Mining Gradual Dependencies Based on Fuzzy Rank Correlation. SMPS Hyung-Won Koh, Eyke Hüllermeier
2010	J	`jnl`	On predictive accuracy and risk minimization in pairwise label ranking. J. Comput. Syst. Sci. Eyke Hüllermeier, Johannes Fürnkranz
2010	B	`conf`	Pattern trees for regression and fuzzy systems modeling. FUZZ-IEEE Robin Senge, Eyke Hüllermeier
2010	—	`conf`	Predicting Partial Orders: Ranking with Abstention. ECML/PKDD (1) Weiwei Cheng, Michaël Rademaker, Bernard De Baets, Eyke Hüllermeier
2010	—	`ch.`	Preference Learning and Ranking by Pairwise Comparison. Preference Learning Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`book`	Preference Learning. Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`ch.`	Preference Learning. Encyclopedia of Machine Learning Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`ch.`	Preference Learning: An Introduction. Preference Learning Johannes Fürnkranz, Eyke Hüllermeier
2010	—	`conf`	Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss. ECML/PKDD (1) Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier
2010	B	`conf`	Similarity measures for protein structures based on fuzzy histogram comparison. FUZZ-IEEE Thomas Fober, Eyke Hüllermeier
2010	—	`conf`	Uncertainty in Clustering and Classification. SUM Eyke Hüllermeier
2009	—	`conf`	A Fuzzy Variant of the Rand Index for Comparing Clustering Structures. IFSA/EUSFLAT Conf. Eyke Hüllermeier, Maria Rifqi
2009	—	`conf`	A New Instance-Based Label Ranking Approach Using the Mallows Model. ISNN (1) Weiwei Cheng, Eyke Hüllermeier
2009	—	`conf`	Binary Decomposition Methods for Multipartite Ranking. ECML/PKDD (1) Johannes Fürnkranz, Eyke Hüllermeier, Stijn Vanderlooy
2009	—	`conf`	Combining Instance-Based Learning and Logistic Regression for Multilabel Classification. LWA Weiwei Cheng, Eyke Hüllermeier
2009	—	`conf`	Combining Instance-Based Learning and Logistic Regression for Multilabel Classification. ECML/PKDD (1) Weiwei Cheng, Eyke Hüllermeier
2009	J	`jnl`	Combining instance-based learning and logistic regression for multilabel classification. Mach. Learn. Weiwei Cheng, Eyke Hüllermeier
2009	A*	`conf`	Decision tree and instance-based learning for label ranking. ICML Weiwei Cheng, Jens C. Huhn, Eyke Hüllermeier
2009	C	`conf`	Efficient Construction of Multiple Geometrical Alignments for the Comparison of Protein Binding Sites. ISDA Thomas Fober, Gerhard Klebe, Eyke Hüllermeier
2009	J	`jnl`	Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. Bioinform. Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier
2009	—	`conf`	Extension and Empirical Comparison of Graph-Kernels for the Analysis of Protein Active Sites. LWA Thomas Fober, Marco Mernberger, Vitalik Melnikov, Ralph Moritz, Eyke Hüllermeier
2009	J	`jnl`	FR3: A Fuzzy Rule Learner for Inducing Reliable Classifiers. IEEE Trans. Fuzzy Syst. Jens C. Huhn, Eyke Hüllermeier
2009	J	`jnl`	FURIA: an algorithm for unordered fuzzy rule induction. Data Min. Knowl. Discov. Jens Christian Hühn, Eyke Hüllermeier
2009	—	`ch.`	Fuzzy Methods in Data Mining. Encyclopedia of Data Warehousing and Mining Eyke Hüllermeier
2009	—	`conf`	Fuzzy Modeling of Labeled Point Cloud Superposition for the Comparison of Protein Binding Sites. IFSA/EUSFLAT Conf. Thomas Fober, Eyke Hüllermeier
2009	J	`jnl`	Fuzzy Operator Trees for Modeling Rating Functions. Int. J. Comput. Intell. Appl. Yu Yi, Thomas Fober, Eyke Hüllermeier
2009	—	`conf`	Graph-Kernels for the Comparative Analysis of Protein Active Sites. GCB Thomas Fober, Marco Mernberger, Ralph Moritz, Eyke Hüllermeier
2009	—	`conf`	Learning Pattern Tree Classifiers Using a Co-Evolutionary Algorithm. LWA Robin Senge, Eyke Hüllermeier
2009	J	`jnl`	Prelude to the papers "Fuzzy case based reasoning for facial expression recognition" and "Temporal similarity by measuring possibilistic uncertainty in CBR". Fuzzy Sets Syst. Eyke Hüllermeier, Michael M. Richter, Rosina Weber
2009	C	`conf`	Similarity Analysis of Protein Binding Sites: A Generalization of the Maximum Common Subgraph Measure Based on Quasi-Clique Detection. ISDA Imen Boukhris, Zied Elouedi, Thomas Fober, Marco Mernberger, Eyke Hüllermeier
2009	J	`jnl`	Supporting Case-Based Retrieval by Similarity Skyline. Künstliche Intell. Eyke Hüllermeier, Ilya Vladimirskiy, Belén Prados-Suárez, Eva Stauch
2009	J	`jnl`	Why Fuzzy Decision Trees are Good Rankers. IEEE Trans. Fuzzy Syst. Eyke Hüllermeier, Stijn Vanderlooy
2008	—	`conf`	A Critical Analysis of Variants of the AUC. ECML/PKDD (1) Stijn Vanderlooy, Eyke Hüllermeier
2008	J	`jnl`	A critical analysis of variants of the AUC. Mach. Learn. Stijn Vanderlooy, Eyke Hüllermeier
2008	J	`jnl`	Case-based learning in a bipolar possibilistic framework. Int. J. Intell. Syst. Jürgen Beringer, Eyke Hüllermeier
2008	—	`conf`	Evolutionary Construction of Multiple Graph Alignments for Mining Structured Biomolecular Data. LWA Thomas Fober, Eyke Hüllermeier, Marco Mernberger
2008	—	`conf`	Evolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules. German Conference on Bioinformatics Thomas Fober, Eyke Hüllermeier, Marco Mernberger
2008	—	`ch.`	Fuzzy Methods for Data Mining and Machine Learning: State ofthe Art and Prospects. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models Eyke Hüllermeier
2008	—	`conf`	Instance-Based Label Ranking using the Mallows Model. ECCBR Workshops Weiwei Cheng, Eyke Hüllermeier
2008	J	`jnl`	Is an ordinal class structure useful in classifier learning? Int. J. Data Min. Model. Manag. Jens C. Huhn, Eyke Hüllermeier
2008	J	`jnl`	Label ranking by learning pairwise preferences. Artif. Intell. Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker
2008	—	`conf`	Learning Similarity Functions from Qualitative Feedback. ECCBR Weiwei Cheng, Eyke Hüllermeier
2008	J	`jnl`	Learning valued preference structures for solving classification problems. Fuzzy Sets Syst. Eyke Hüllermeier, Klaus Brinker
2008	J	`jnl`	Multilabel classification via calibrated label ranking. Mach. Learn. Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Klaus Brinker
2008	—	`conf`	Preface: Uncertainty, Similarity, and Knowledge Discovery in CBR. ECCBR Workshops Eyke Hüllermeier, Michael M. Richter, Rosina Weber, Kerstin Bach, Miltos Petridis
2008	—	`conf`	Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions. ECCBR Eyke Hüllermeier, Ilya Vladimirskiy, Belén Prados-Suárez, Eva Stauch
2008	—	`conf`	Weighted Voting as Approximate MAP Prediction in Pairwise Classification. LWA Eyke Hüllermeier, Stijn Vanderlooy
2007	J	`jnl`	A fuzzy-probabilistic earthquake risk assessment system. Soft Comput. Iman Karimi, Eyke Hüllermeier, Konstantin Meskouris
2007	B	`conf`	Adaptive Optimization of the Number of Clusters in Fuzzy Clustering. FUZZ-IEEE Jürgen Beringer, Eyke Hüllermeier
2007	A*	`conf`	An Efficient Algorithm for Instance-Based Learning on Data Streams. ICDM Jürgen Beringer, Eyke Hüllermeier
2007	—	`book`	Case-Based Approximate Reasoning Eyke Hüllermeier
2007	A*	`conf`	Case-Based Multilabel Ranking. IJCAI Klaus Brinker, Eyke Hüllermeier
2007	J	`jnl`	Comparing probability measures using possibility theory: A notion of relative peakedness. Int. J. Approx. Reason. Didier Dubois, Eyke Hüllermeier
2007	J	`jnl`	Credible Case-Based Inference Using Similarity Profiles. IEEE Trans. Knowl. Data Eng. Eyke Hüllermeier
2007	J	`jnl`	Editorial. Int. J. Uncertain. Fuzziness Knowl. Based Syst. Eyke Hüllermeier, Frank Klawonn, Andreas Nürnberger
2007	J	`jnl`	Efficient instance-based learning on data streams. Intell. Data Anal. Jürgen Beringer, Eyke Hüllermeier
2007	—	`conf`	Fuzzy-Relational Classification: Combining Pairwise Decomposition Techniques with Fuzzy Preference Modeling. EUSFLAT Conf. (1) Eyke Hüllermeier, Klaus Brinker
2007	B	`conf`	Graph Alignment: Fuzzy Pattern Mining for the Structural Analysis of Protein Active Sites. FUZZ-IEEE Eyke Hüllermeier, Nils Weskamp, Gerhard Klebe, Daniel Kuhn
2007	J	`jnl`	In Defense of Fuzzy Association Analysis. IEEE Trans. Syst. Man Cybern. Part B Eyke Hüllermeier, Yu Yi
2007	—	`conf`	Interactive Ranking of Skylines Using Machine Learning Techniques. LWA Weiwei Cheng, Eyke Hüllermeier, Bernhard Seeger, Ilya Vladimirskiy
2007	C	`conf`	Label Ranking in Case-Based Reasoning. ICCBR Klaus Brinker, Eyke Hüllermeier
2007	J	`jnl`	Multiple Graph Alignment for the Structural Analysis of Protein Active Sites. IEEE ACM Trans. Comput. Biol. Bioinform. Nils Weskamp, Eyke Hüllermeier, Daniel Kuhn, Gerhard Klebe
2007	—	`conf`	On Minimizing the Position Error in Label Ranking. ECML Eyke Hüllermeier, Johannes Fürnkranz
2007	—	`conf`	On Pairwise Naive Bayes Classifiers. ECML Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyke Hüllermeier
2007	J	`jnl`	Risk assessment system of natural hazards: A new approach based on fuzzy probability. Fuzzy Sets Syst. Iman Karimi, Eyke Hüllermeier
2007	J	`jnl`	Special Issue on Soft Computing for Information Mining. Soft Comput. Ulrich Bodenhofer, Eyke Hüllermeier, Frank Klawonn, Rudolf Kruse
2006	A	`conf`	A Unified Model for Multilabel Classification and Ranking. ECAI Klaus Brinker, Johannes Fürnkranz, Eyke Hüllermeier
2006	J	`jnl`	A systematic approach to the assessment of fuzzy association rules. Data Min. Knowl. Discov. Didier Dubois, Eyke Hüllermeier, Henri Prade
2006	—	`conf`	Case-Based Label Ranking. ECML Klaus Brinker, Eyke Hüllermeier
2006	J	`jnl`	Fuzzy methods for case-based recommendation and decision support. J. Intell. Inf. Syst. Didier Dubois, Eyke Hüllermeier, Henri Prade
2006	A*	`conf`	Hierarchical Classification by Expected Utility Maximization. ICDM Korinna Bade, Eyke Hüllermeier, Andreas Nürnberger
2006	J	`jnl`	Learning from ambiguously labeled examples. Intell. Data Anal. Eyke Hüllermeier, Jürgen Beringer
2006	J	`jnl`	Online clustering of parallel data streams. Data Knowl. Eng. Jürgen Beringer, Eyke Hüllermeier
2005	C	`conf`	A Notion of Comparative Probabilistic Entropy Based on the Possibilistic Specificity Ordering. ECSQARU Didier Dubois, Eyke Hüllermeier
2005	A*	`conf`	Cho-k-NN: A Method for Combining Interacting Pieces of Evidence in Case-Based Learning. IJCAI Eyke Hüllermeier
2005	J	`jnl`	Clustering of gene expression data using a local shape-based similarity measure. Bioinform. Rajarajeswari Balasubramaniyan, Eyke Hüllermeier, Nils Weskamp, Jörg Kämper
2005	J	`jnl`	Experience-Based Decision Making: A Satisficing Decision Tree Approach. IEEE Trans. Syst. Man Cybern. Part A Eyke Hüllermeier
2005	J	`jnl`	Fuzzy methods in machine learning and data mining: Status and prospects. Fuzzy Sets Syst. Eyke Hüllermeier
2005	—	`conf`	Improving the interpretability of data-driven evolving fuzzy systems. EUSFLAT Conf. Edwin Lughofer, Eyke Hüllermeier, Erich-Peter Klement
2005	—	`conf`	Learning Complexity-Bounded Rule-Based Classifiers by Combining. Association Analysis and Genetic Algorithms. EUSFLAT Conf. Yu Yi, Eyke Hüllermeier
2005	B	`conf`	Learning Label Preferences: Ranking Error Versus Position Error. IDA Eyke Hüllermeier, Johannes Fürnkranz
2005	B	`conf`	Learning from Ambiguously Labeled Examples. IDA Eyke Hüllermeier, Jürgen Beringer
2005	—	`conf`	On Position Error and Label Ranking through Iterated Choice. LWA Eyke Hüllermeier, Johannes Fürnkranz, Jürgen Beringer
2005	J	`jnl`	Preference Learning. Künstliche Intell. Johannes Fürnkranz, Eyke Hüllermeier
2005	J	`jnl`	Special issue on fuzzy sets in knowledge discovery. Fuzzy Sets Syst. Eyke Hüllermeier
2004	J	`jnl`	26. Jahrestagung Künstliche Intelligenz (KI-2003). Künstliche Intell. Eyke Hüllermeier
2004	J	`jnl`	Efficient similarity search in protein structure databases by k-clique hashing. Bioinform. Nils Weskamp, Daniel Kuhn, Eyke Hüllermeier, Gerhard Klebe
2004	J	`jnl`	Flexible constraints for regularization in learning from data. Int. J. Intell. Syst. Eyke Hüllermeier
2004	—	`conf`	Fuzzy Methods in Knowledge Discovery. Fuzzy Days Eyke Hüllermeier
2004	—	`conf`	Graph Alignments: A New Concept to Detect Conserved Regions in Protein Active Sites. German Conference on Bioinformatics Nils Weskamp, Eyke Hüllermeier, Daniel Kuhn, Gerhard Klebe
2004	A	`conf`	Instance-Based Prediction with Guaranteed Confidence. ECAI Eyke Hüllermeier
2004	B	`conf`	Ranking by pairwise comparison a note on risk minimization. FUZZ-IEEE Eyke Hüllermeier, Johannes Fürnkranz
2003	C	`conf`	A Note on Quality Measures for Fuzzy Asscociation Rules. IFSA Didier Dubois, Eyke Hüllermeier, Henri Prade
2003	—	`conf`	Efficient Similarity Search in Protein Structure Databases: Improving Cliqae-Detection through Clique Hashing. German Conference on Bioinformatics Nils Weskamp, Daniel Kuhn, Eyke Hüllermeier, Gerhard Klebe
2003	J	`jnl`	Flexibility and Fuzzy Case-Based Evaluation in Querying: An Illustration in an Experimental Setting. Int. J. Uncertain. Fuzziness Knowl. Based Syst. Martine de Calmès, Didier Dubois, Eyke Hüllermeier, Henri Prade, Florence Sèdes
2003	C	`conf`	Inducing Fuzzy Concepts through Extended Version Space Learning. IFSA Eyke Hüllermeier
2003	Misc	`conf`	Instance-Based Learning of Credible Label Sets. KI Eyke Hüllermeier
2003	—	`conf`	Instance-based collaborative filtering with fuzzy labels. EUSFLAT Conf. Eyke Hüllermeier
2003	J	`jnl`	On the representation of fuzzy rules in terms of crisp rules. Inf. Sci. Didier Dubois, Eyke Hüllermeier, Henri Prade
2003	—	`conf`	Pairwise Preference Learning and Ranking. ECML Johannes Fürnkranz, Eyke Hüllermeier
2003	J	`jnl`	Possibilistic instance-based learning. Artif. Intell. Eyke Hüllermeier
2003	B	`conf`	Regularized Learning with Flexible Constraints. IDA Eyke Hüllermeier
2003	—	`ch.`	Sequential Decision Making in Heuristic Search. Planning Based on Decision Theory Eyke Hüllermeier
2002	A*	`conf`	A Fuzzy Approach to Flexible Case-based Querying: Methodology and Experimentation. KR Martine de Calmès, Didier Dubois, Eyke Hüllermeier, Henri Prade, Florence Sèdes
2002	—	`conf`	Association Rules for Expressing Gradual Dependencies. PKDD Eyke Hüllermeier
2002	B	`conf`	Case-based querying and prediction: a fuzzy set approach. FUZZ-IEEE Martine de Calmès, Didier Dubois, Eyke Hüllermeier, Henri Prade, Florence Sèdes
2002	B	`conf`	Exploiting similarity and experience in decision making. FUZZ-IEEE Eyke Hüllermeier
2002	J	`jnl`	Fuzzy set-based methods in instance-based reasoning. IEEE Trans. Fuzzy Syst. Didier Dubois, Eyke Hüllermeier, Henri Prade
2002	J	`jnl`	Model adaptation in possibilistic instance-based reasoning. IEEE Trans. Fuzzy Syst. Eyke Hüllermeier, Didier Dubois, Henri Prade
2002	A	`conf`	On the Representation and Combination of Evidence in Instance-Based Learning. ECAI Eyke Hüllermeier
2002	—	`conf`	Possibilistic Induction in Decision-Tree Learning. ECML Eyke Hüllermeier
2001	—	`ch.`	Formalizing Case Based Inference Using Fuzzy Rules. Soft Computing in Case Based Reasoning Eyke Hüllermeier, Didier Dubois, Henri Prade
2001	—	`conf`	Fuzzy Association Rules: Semantic Issues and Quality Measures. Fuzzy Days Eyke Hüllermeier
2001	—	`conf`	Implication-Based Fuzzy Association Rules. PKDD Eyke Hüllermeier
2001	J	`jnl`	Similarity-based inference as evidential reasoning. Int. J. Approx. Reason. Eyke Hüllermeier
2000	—	`conf`	A Method for Predicting Solutions in Case-Based Problem Solving. EWCBR Eyke Hüllermeier
2000	—	`conf`	Change Detection in Heuristic Search. AAAI/IAAI Eyke Hüllermeier
2000	—	`conf`	Flexible Control of Case-Based Prediction in the Framework of Possibility Theory. EWCBR Didier Dubois, Eyke Hüllermeier, Henri Prade
2000	A	`conf`	Focusing Search by Using Problem Solving Experience. ECAI Eyke Hüllermeier
2000	A	`conf`	Similarity-based Inference as Evitential Reasoning. ECAI Eyke Hüllermeier
1999	—	`conf`	A Possibilistic Formalization of Case-Based Reasoning and Decision Making. Fuzzy Days Eyke Hüllermeier
1999	J	`jnl`	Approximation of uncertain functional relationships. Fuzzy Sets Syst. Eyke Hüllermeier
1999	B	`conf`	Exploiting Similarity for Supporting Data Analysis and Problem Solving. IDA Eyke Hüllermeier
1999	J	`jnl`	Numerical Methods for Fuzzy Initial Value Problems. Int. J. Uncertain. Fuzziness Knowl. Based Syst. Eyke Hüllermeier
1999	A*	`conf`	Toward a Probabilistic Formalization of Case-Based Inference. IJCAI Eyke Hüllermeier
1997	J	`jnl`	An Approach to Modelling and Simulation of Uncertain Dynamical Systems. Int. J. Uncertain. Fuzziness Knowl. Based Syst. Eyke Hüllermeier
1997	—	`—`	Reasoning about systems based on incomplete and uncertain models. Eyke Hüllermeier