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448 Publications
2023 | Preprint | LibreCat-ID: 45911 | 
Lienen, Julian, and Eyke Hüllermeier. “Mitigating Label Noise through Data Ambiguation.” ArXiv:2305.13764, 2023.
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| arXiv
2023 | Journal Article | LibreCat-ID: 21600
Dellnitz, Michael, et al. “Efficient Time Stepping for Numerical Integration Using Reinforcement Learning.” SIAM Journal on Scientific Computing, vol. 45, no. 2, 2023, pp. A579–95, doi:10.1137/21M1412682.
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| arXiv
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, 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.” ESANN 2023 Proceedings, i6doc.com publ., 2023, doi:10.14428/esann/2023.es2023-148.
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2023 | Book Chapter | LibreCat-ID: 48778
Muschalik, Maximilian, et al. “IPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios.” Communications in Computer and Information Science, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-44064-9_11.
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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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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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| DOI
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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| DOI
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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| DOI
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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