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8 Publications
2022 | Journal Article | LibreCat-ID: 48780
M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “Agnostic Explanation of Model Change based on Feature Importance,” KI - Künstliche Intelligenz, vol. 36, no. 3–4, pp. 211–224, 2022, doi: 10.1007/s13218-022-00766-6.
LibreCat
| DOI
2023 | Journal Article | LibreCat-ID: 48779
A. Artelt, R. Visser, and B. Hammer, “‘I do not know! but why?’ — Local model-agnostic example-based explanations of reject,” Neurocomputing, vol. 558, Art. no. 126722, 2023, doi: 10.1016/j.neucom.2023.126722.
LibreCat
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2023 | Book Chapter | LibreCat-ID: 48776
M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams,” in Machine Learning and Knowledge Discovery in Databases: Research Track, Cham: Springer Nature Switzerland, 2023.
LibreCat
| DOI
2023 | Journal Article | LibreCat-ID: 50262
F. Fumagalli, M. Muschalik, E. Hüllermeier, and B. Hammer, “Incremental permutation feature importance (iPFI): towards online explanations on data streams,” Machine Learning, vol. 112, no. 12, pp. 4863–4903, 2023, doi: 10.1007/s10994-023-06385-y.
LibreCat
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2023 | Conference Paper | LibreCat-ID: 48775
F. Fumagalli, M. Muschalik, E. Hüllermeier, and B. Hammer, “On Feature Removal for Explainability in Dynamic Environments,” presented at the ESANN 2023 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges (Belgium) and online, 2023, doi: 10.14428/esann/2023.es2023-148.
LibreCat
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2023 | Conference Paper | LibreCat-ID: 52230
F. Fumagalli, M. Muschalik, P. Kolpaczki, E. Hüllermeier, and B. Hammer, “SHAP-IQ: Unified Approximation of any-order Shapley Interactions,” in NeurIPS 2023 - Advances in Neural Information Processing Systems, 2023, vol. 36, pp. 11515--11551.
LibreCat
2024 | Journal Article | LibreCat-ID: 53073
M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 13, pp. 14388–14396, 2024, doi: 10.1609/aaai.v38i13.29352.
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