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448 Publications
2024 | Journal Article | LibreCat-ID: 53073
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. Proceedings of the AAAI Conference on Artificial Intelligence, 38(13), 14388–14396. https://doi.org/10.1609/aaai.v38i13.29352
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| DOI
2024 | Journal Article | LibreCat-ID: 54911
Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 54910
Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190
LibreCat
| DOI
2024 | Conference Paper | LibreCat-ID: 55311
Kolpaczki, P., Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. In S. Dasgupta, S. Mandt, & Y. Li (Eds.), Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (Vol. 238, pp. 3520–3528). PMLR.
LibreCat
2024 | Journal Article | LibreCat-ID: 54907
Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190
LibreCat
| DOI
2024 | Conference Paper | LibreCat-ID: 57645
Heid, S., Kornowicz, J., Hanselle, J. M., Hüllermeier, E., & Thommes, K. (2024). Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems. PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, 21, 233.
LibreCat
2024 | Conference Paper | LibreCat-ID: 55631
Javanmardi, A., Aimiyekagbon, O. K., Bender, A., Kimotho, J. K., Sextro, W., & Hüllermeier, E. (2024). Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions. PHM Society European Conference, 8(1), Article 9. https://doi.org/10.36001/phme.2024.v8i1.4101
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| DOI
2023 | Conference Paper | LibreCat-ID: 51373
Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2023). Probabilistic Scoring Lists for Interpretable Machine Learning. 26th International Conference on Discovery Science , 14050, 189–203. https://doi.org/10.1007/978-3-031-45275-8_13
LibreCat
| DOI
2023 | Conference Paper | LibreCat-ID: 52230
Fumagalli, F., Muschalik, M., Kolpaczki, P., Hüllermeier, E., & Hammer, B. (2023). SHAP-IQ: Unified Approximation of any-order Shapley Interactions. NeurIPS 2023 - Advances in Neural Information Processing Systems, 36, 11515--11551.
LibreCat
2023 | Book Chapter | LibreCat-ID: 54613
Hanselle, J. M., Hüllermeier, E., Mohr, F., Ngonga Ngomo, A.-C., Sherif, M., Tornede, A., & Wever, M. D. (2023). Configuration and Evaluation. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing – Individualized IT-services in dynamic markets (Vol. 412, pp. 85–104). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068466
LibreCat
| DOI
2023 | Book Chapter | LibreCat-ID: 54909
Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2023). Probabilistic Scoring Lists for Interpretable Machine Learning. In Discovery Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-45275-8_13
LibreCat
| DOI
2023 | Preprint | LibreCat-ID: 44512 |

Uhlemeyer, S., Lienen, J., Hüllermeier, E., & Gottschalk, H. (2023). Detecting Novelties with Empty Classes. In arXiv:2305.00983.
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| arXiv
2023 | Conference Paper | LibreCat-ID: 31880 |

Nguyen, D. A., Levie, R., Lienen, J., Kutyniok, G., & Hüllermeier, E. (2023). Memorization-Dilation: Modeling Neural Collapse Under Noise. International Conference on Learning Representations, ICLR. International Conference on Learning Representations, ICLR, Kigali, Ruanda.
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2023 | Book Chapter | LibreCat-ID: 45884 |

Hanselle, J. M., Hüllermeier, E., Mohr, F., Ngonga Ngomo, A.-C., Sherif, M., Tornede, A., & Wever, M. D. (2023). Configuration and Evaluation. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 85–104). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068466
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2023 | Book Chapter | LibreCat-ID: 45886 |

Wehrheim, H., Hüllermeier, E., Becker, S., Becker, M., Richter, C., & Sharma, A. (2023). Composition Analysis in Unknown Contexts. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 105–123). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068510
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2023 | Preprint | LibreCat-ID: 45911 |

Lienen, J., & Hüllermeier, E. (2023). Mitigating Label Noise through Data Ambiguation. In arXiv:2305.13764.
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| arXiv
2023 | Journal Article | LibreCat-ID: 21600
Dellnitz, M., Hüllermeier, E., Lücke, M., Ober-Blöbaum, S., Offen, C., Peitz, S., & Pfannschmidt, K. (2023). Efficient time stepping for numerical integration using reinforcement learning. SIAM Journal on Scientific Computing, 45(2), A579–A595. https://doi.org/10.1137/21M1412682
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| arXiv
2023 | Book Chapter | LibreCat-ID: 48776
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2023). 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. https://doi.org/10.1007/978-3-031-43418-1_26
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| DOI
2023 | Conference Paper | LibreCat-ID: 48775
Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). On Feature Removal for Explainability in Dynamic Environments. ESANN 2023 Proceedings. ESANN 2023 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges (Belgium) and online. https://doi.org/10.14428/esann/2023.es2023-148
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| DOI
2023 | Book Chapter | LibreCat-ID: 48778
Muschalik, M., Fumagalli, F., Jagtani, R., Hammer, B., & Huellermeier, E. (2023). iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. In Communications in Computer and Information Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-44064-9_11
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