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452 Publications
2023 | Conference Paper | LibreCat-ID: 51209
Hanselle, Jonas Manuel, et al. “Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain.” LWDA’23: Learning, Knowledge, Data, Analysis. , edited by M Leyer and J Wichmann, 2023.
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2023 | Conference Paper | LibreCat-ID: 48778
Muschalik, Maximilian, et al. “IPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios.” Proceedings of the World Conference on Explainable Artificial Intelligence (XAI), 2023, doi:10.1007/978-3-031-44064-9_11.
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2023 | Book Chapter | LibreCat-ID: 48776
Muschalik, Maximilian, et al. “ISAGE: An Incremental Version of SAGE for Online Explanation on Data Streams.” Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference (ECML PKDD), Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-43418-1_26.
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2023 | Conference Paper | LibreCat-ID: 48775
Fumagalli, Fabian, et al. “On Feature Removal for Explainability in Dynamic Environments.” Proceedings of the European Symposium on Artificial Neural Networks (ESANN), 2023, doi:10.14428/ESANN/2023.ES2023-148.
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2023 | Conference Paper | LibreCat-ID: 52230
Fumagalli, Fabian, et al. “SHAP-IQ: Unified Approximation of Any-Order Shapley Interactions.” Advances in Neural Information Processing Systems (NeurIPS), vol. 36, 2023, pp. 11515--11551.
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2022 | Conference Paper | LibreCat-ID: 32311
Sharma, Arnab, et al. “Property-Driven Testing of Black-Box Functions.” Proceedings of the 10th IEEE/ACM International Conference on Formal Methods in Software Engineering (FormaliSE), IEEE, 2022, pp. 113–23.
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2022 | Conference Paper | LibreCat-ID: 34542
Campagner, Andrea, et al. “Scikit-Weak: A Python Library for Weakly Supervised Machine Learning.” Lecture Notes in Computer Science, vol. 13633, Springer, 2022, pp. 57–70.
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2022 | Preprint | LibreCat-ID: 31546 | 
Lienen, Julian, et al. “Conformal Credal Self-Supervised Learning.” ArXiv:2205.15239, 2022.
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2022 | Journal Article | LibreCat-ID: 33090
Gevers, Karina, et al. “A Comparison of Heuristic, Statistical, and Machine Learning Methods for Heated Tool Butt Welding of Two Different Materials.” Welding in the World, Springer Science and Business Media LLC, 2022, doi:10.1007/s40194-022-01339-9.
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2022 | Report | LibreCat-ID: 36227
Hammer, Barbara, 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.
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2022 | Journal Article | LibreCat-ID: 48780
Muschalik, Maximilian, et al. “Agnostic Explanation of Model Change Based on Feature Importance.” KI - Künstliche Intelligenz, vol. 36, no. 3–4, Springer Science and Business Media LLC, 2022, pp. 211–24, doi:10.1007/s13218-022-00766-6.
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2021 | Journal Article | LibreCat-ID: 24143
Drees, Jan Peter, et al. “Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!” 14th ACM Workshop on Artificial Intelligence and Security, 2021.
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2021 | Journal Article | LibreCat-ID: 24148
Ramaswamy, Arunselvan, and Eyke Hüllermeier. “Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis.” IEEE Transactions on Artificial Intelligence (to Appear), 2021.
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2021 | Journal Article | LibreCat-ID: 21004
Wever, Marcel Dominik, et al. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, pp. 1–1, doi:10.1109/tpami.2021.3051276.
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2021 | Journal Article | LibreCat-ID: 21092
Mohr, Felix, et al. “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning.” IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE.
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2021 | Conference Paper | LibreCat-ID: 21570
Tornede, Tanja, et al. “Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance.” Proceedings of the Genetic and Evolutionary Computation Conference, 2021.
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2021 | Journal Article | LibreCat-ID: 21636
Lienen, Julian, and Eyke Hüllermeier. “Instance Weighting through Data Imprecisiation.” International Journal of Approximate Reasoning, Elsevier, 2021.
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