Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. Proceedings of the AAAI Conference on Artificial Intelligence. 2024;38(13):14388-14396. doi:10.1609/aaai.v38i13.29352
LibreCat: /record/53073
DOI: 10.1609/aaai.v38i13.29352

Uhlemeyer S, Lienen J, Hüllermeier E, Gottschalk H. Detecting Novelties with Empty Classes. arXiv:230500983. Published online 2023.
LibreCat: /record/44512
arXiv: 2305.00983

Nguyen DA, Levie R, Lienen J, Kutyniok G, Hüllermeier E. Memorization-Dilation: Modeling Neural Collapse Under Noise. In: International Conference on Learning Representations, ICLR. ; 2023.
LibreCat: /record/31880

Hanselle JM, Hüllermeier E, Mohr F, et al. Configuration and Evaluation. In: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:85-104. doi:10.5281/zenodo.8068466
LibreCat: /record/45884
DOI: 10.5281/zenodo.8068466

Wehrheim H, Hüllermeier E, Becker S, Becker M, Richter C, Sharma A. Composition Analysis in Unknown Contexts. In: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:105-123. doi:10.5281/zenodo.8068510
LibreCat: /record/45886
DOI: 10.5281/zenodo.8068510

Lienen J, Hüllermeier E. Mitigating Label Noise through Data Ambiguation. arXiv:230513764. Published online 2023.
LibreCat: /record/45911
arXiv: 2305.13764

Dellnitz M, Hüllermeier E, Lücke M, et al. Efficient time stepping for numerical integration using reinforcement  learning. SIAM Journal on Scientific Computing. 2023;45(2):9-5. doi:10.1137/21M1412682
LibreCat: /record/21600
DOI: 10.1137/21M1412682
arXiv: arXiv:2104.03562

Hanselle JM, Fürnkranz J, Hüllermeier E. Probabilistic Scoring Lists for Interpretable Machine Learning. In: 26th International Conference on Discovery Science . Vol 14050. Lecture Notes in Computer Science. Springer Nature Switzerland; 2023:189-203. doi:10.1007/978-3-031-45275-8_13
LibreCat: /record/51373
DOI: 10.1007/978-3-031-45275-8_13

Muschalik M, Fumagalli F, Hammer B, Huellermeier E. iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. In: Machine Learning and Knowledge Discovery in Databases: Research Track. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-43418-1_26
LibreCat: /record/48776
DOI: 10.1007/978-3-031-43418-1_26

Muschalik M, Fumagalli F, Jagtani R, Hammer B, Huellermeier E. iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. In: Communications in Computer and Information Science. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-44064-9_11
LibreCat: /record/48778
DOI: 10.1007/978-3-031-44064-9_11

Fumagalli F, Muschalik M, Hüllermeier E, Hammer B. On Feature Removal for Explainability in Dynamic Environments. In: ESANN 2023 Proceedings. i6doc.com publ.; 2023. doi:10.14428/esann/2023.es2023-148
LibreCat: /record/48775
DOI: 10.14428/esann/2023.es2023-148

Fumagalli F, Muschalik M, Kolpaczki P, Hüllermeier E, Hammer B. SHAP-IQ: Unified Approximation of any-order Shapley Interactions. In: NeurIPS 2023 - Advances in Neural Information Processing Systems. Vol 36. Curran Associates, Inc.; 2023:11515--11551.
LibreCat: /record/52230

Schede E, Brandt J, Tornede A, et al. A Survey of Methods for Automated Algorithm Configuration. arXiv:220201651. Published online 2022.
LibreCat: /record/30868
arXiv: 2202.01651

Sharma A, Melnikov V, Hüllermeier E, Wehrheim H. Property-Driven Testing of Black-Box Functions. In: Proceedings of the 10th IEEE/ACM International Conference on Formal Methods in Software Engineering (FormaliSE). IEEE; 2022:113-123.
LibreCat: /record/32311

Campagner A, Lienen J, Hüllermeier E, Ciucci D. Scikit-Weak: A Python Library for Weakly Supervised Machine Learning. In: Lecture Notes in Computer Science. Vol 13633. Springer; 2022:57-70.
LibreCat: /record/34542

Lienen J, Demir C, Hüllermeier E. Conformal Credal Self-Supervised Learning. arXiv:220515239. Published online 2022.
LibreCat: /record/31546

Tornede A, Bengs V, Hüllermeier E. Machine Learning for Online Algorithm Selection under Censored Feedback. Proceedings of the 36th AAAI Conference on Artificial Intelligence. Published online 2022.
LibreCat: /record/30867
arXiv: 2109.06234

Tornede A, Gehring L, Tornede T, Wever MD, Hüllermeier E. Algorithm Selection on a Meta Level. Machine Learning. Published online 2022.
LibreCat: /record/30865
arXiv: 2107.09414

Gevers K, Tornede A, Wever MD, Schöppner V, Hüllermeier E. A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials. Welding in the World. Published online 2022. doi:10.1007/s40194-022-01339-9
LibreCat: /record/33090
DOI: 10.1007/s40194-022-01339-9

Hammer B, Hüllermeier E, Lohweg V, et al. Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens.; 2022. doi:10.4119/unibi/2965622
LibreCat: /record/36227
DOI: 10.4119/unibi/2965622