← Authors

Eyke Hüllermeier

68 papers · 2011–2026 · 12 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer 🌍 Conference Polyglot (12) 🐝 Cross-Pollinator (11) 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (14) 🗺️ Taxonomy Completionist (19) 🤝 Dynamic Duo (18) 👑 Triple Crown 🏆 Keyword Champion (3) 🏆 Grand Slam 🔬 Deep Specialist (11) 🗃️ Keyword Collector (55) 📈 Trend Setter 🔥 Unstoppable (15) 🚀 Conference Pioneer ⚡ Prolific Year (6) 💎 Century Club (65) ❓ The Questioner (3)

Conferences

ICML (13) AAAI (12) NIPS (12) UAI (8) IJCAI (5) ACML (4) AISTATS (4) ICLR (4) EMNLP (2) JMLR (2) CVPR (1) NAACL (1)

Top co-authors

Viktor Bengs (18) Maximilian Muschalik (10) Barbara Hammer (9) Fabian Fumagalli (9) Willem Waegeman (8) Róbert Busa-Fekete (7) Yusuf Sale (6) Patrick Kolpaczki (6) Julian Lienen (6) Jasmin Brandt (5)

Keywords

epistemic uncertainty (11) multi-armed bandit (8) aleatoric uncertainty (8) uncertainty quantification (7) shapley value (7) dueling bandit (6) feature attribution (6) online learning (5) plackett-luce model (5) credal set (4) preference learning (4) multi-label classification (4) pairwise preference (3) probability distribution (3) model interpretability (3) sample complexity (3) regret bound (3) hyperparameter optimization (3) combinatorial optimization (3) pairwise comparison (3)

Papers

Fine-grained Uncertainty Decomposition in Large Language Models: A Spectral Approach AAAI 2026
Shapley Value Approximation Based on k-Additive Games AAAI 2026
Uncertainty Quantification for Machine Learning: One Size Does Not Fit All AAAI 2026
DUO: Diverse, Uncertain, On-Policy Query Generation and Selection for Reinforcement Learning from Human Feedback AAAI 2025
Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions EMNLP 2025
X-Hacking: The Threat of Misguided AutoML ICML 2025
Inverse Constitutional AI: Compressing Preferences into Principles ICLR 2025
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks ICLR 2025
Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection NAACL 2025
Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries ICML 2025
Conformal Prediction without Nonconformity Scores UAI 2025
Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory AISTATS 2025
Position: Why We Must Rethink Empirical Research in Machine Learning ICML 2024
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions ICML 2024
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification AISTATS 2024
Identifying Copeland Winners in Dueling Bandits with Indifferences AISTATS 2024
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization ICLR 2024
Label-wise Aleatoric and Epistemic Uncertainty Quantification UAI 2024
Linear Opinion Pooling for Uncertainty Quantification on Graphs UAI 2024
Conformalized Credal Set Predictors NIPS 2024
shapiq: Shapley Interactions for Machine Learning NIPS 2024
Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO IJCAI 2024
Second-Order Uncertainty Quantification: A Distance-Based Approach ICML 2024
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? ICML 2024
Approximating the Shapley Value without Marginal Contributions AAAI 2024
Mitigating Label Noise through Data Ambiguation AAAI 2024
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles AAAI 2024
AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration AAAI 2023
SHAP-IQ: Unified Approximation of any-order Shapley Interactions NIPS 2023
Koopman Kernel Regression NIPS 2023
On the Calibration of Probabilistic Classifier Sets AISTATS 2023
Memorization-Dilation: Modeling Neural Collapse Under Noise ICLR 2023
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification ICML 2023
A Survey of Methods for Automated Algorithm Configuration (Extended Abstract) IJCAI 2023
Is the volume of a credal set a good measure for epistemic uncertainty? UAI 2023
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures? UAI 2023
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget NIPS 2022
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation NIPS 2022
Machine Learning for Online Algorithm Selection under Censored Feedback AAAI 2022
Set-valued prediction in hierarchical classification with constrained representation complexity UAI 2022
Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison UAI 2022
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models ICML 2022
From Label Smoothing to Label Relaxation AAAI 2021
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits NIPS 2021
Credal Self-Supervised Learning NIPS 2021
Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model AAAI 2021
Robust Regression for Monocular Depth Estimation ACML 2021
Monocular Depth Estimation via Listwise Ranking Using the Plackett-Luce Model CVPR 2021
Preference-based Online Learning with Dueling Bandits: A Survey JMLR 2021
Testification of Condorcet Winners in dueling bandits UAI 2021
A Novel Higher-order Weisfeiler-Lehman Graph Convolution ACML 2020
Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals IJCAI 2020
Reliable Multilabel Classification: Prediction with Partial Abstention AAAI 2020
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis ACML 2020
Preselection Bandits ICML 2020
Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA ACML 2019
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty IJCAI 2018
Ranking Distributions based on Noisy Sorting ICML 2018
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening ICML 2017
Extreme F-measure Maximization using Sparse Probability Estimates ICML 2016
Online F-Measure Optimization NIPS 2015
Qualitative Multi-Armed Bandits: A Quantile-Based Approach ICML 2015
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach NIPS 2015
On the Bayes-Optimality of F-Measure Maximizers JMLR 2014
Learning to Rank Lexical Substitutions EMNLP 2013
Preference-Based CBR: General Ideas and Basic Principles IJCAI 2013
Label Ranking with Partial Abstention based on Thresholded Probabilistic Models NIPS 2012
An Exact Algorithm for F-Measure Maximization NIPS 2011