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440 Publications
2022 | Report | LibreCat-ID: 36227
Hammer, B., Hüllermeier, E., Lohweg, V., Schneider, A., Schenck, W., Kuhl, U., Braun, M., Pfeifer, A., Holst, C.-A., Schmidt, M., Schomaker, G., & Tornede, T. (2022). Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens. https://doi.org/10.4119/unibi/2965622
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| DOI
2022 | Journal Article | LibreCat-ID: 48780
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2022). Agnostic Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz, 36(3–4), 211–224. https://doi.org/10.1007/s13218-022-00766-6
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| DOI
2021 | Journal Article | LibreCat-ID: 24143
Drees, J. P., Gupta, P., Hüllermeier, E., Jager, T., Konze, A., Priesterjahn, C., Ramaswamy, A., & Somorovsky, J. (2021). Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs! 14th ACM Workshop on Artificial Intelligence and Security.
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2021 | Journal Article | LibreCat-ID: 24148
Ramaswamy, A., & Hüllermeier, E. (2021). Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis. IEEE Transactions on Artificial Intelligence (to Appear).
LibreCat
2021 | Journal Article | LibreCat-ID: 21004
Wever, M. D., Tornede, A., Mohr, F., & Hüllermeier, E. (2021). AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–1. https://doi.org/10.1109/tpami.2021.3051276
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| DOI
2021 | Journal Article | LibreCat-ID: 21092
Mohr, F., Wever, M. D., Tornede, A., & Hüllermeier, E. (n.d.). Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence.
LibreCat
2021 | Conference Paper | LibreCat-ID: 21570
Tornede, T., Tornede, A., Wever, M. D., & Hüllermeier, E. (2021). Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance. Proceedings of the Genetic and Evolutionary Computation Conference. Genetic and Evolutionary Computation Conference.
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2021 | Journal Article | LibreCat-ID: 21636
Lienen, J., & Hüllermeier, E. (2021). Instance weighting through data imprecisiation. International Journal of Approximate Reasoning.
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2021 | Conference Paper | LibreCat-ID: 21637 | 
Lienen, J., & Hüllermeier, E. (2021). From Label Smoothing to Label Relaxation. In Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI (Vol. 35, pp. 8583–8591). Online: AAAI Press.
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2021 | Conference Paper | LibreCat-ID: 23779
Bernijazov, R., Dicks, A., Dumitrescu, R., Foullois, M., Hanselle, J. M., Hüllermeier, E., Karakaya, G., Ködding, P., Lohweg, V., Malatyali, M., Meyer auf der Heide, F., Panzner, M., & Soltenborn, C. (2021). A Meta-Review on Artificial Intelligence in Product Creation. Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21). 30th International Joint Conference on Artificial Intelligence (IJCAI 2021) - Workshop “AI and Product Design,” Montreal, Kanada.
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2021 | Conference Paper | LibreCat-ID: 22280
Lienen, J., Hüllermeier, E., Ewerth, R., & Nommensen, N. (2021). Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 14595–14604.
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2021 | Preprint | LibreCat-ID: 22509 |
Lienen, J., & Hüllermeier, E. (2021). Credal Self-Supervised Learning. ArXiv:2106.11853.
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2021 | Conference Paper | LibreCat-ID: 22913
Hüllermeier, E., Mohr, F., Tornede, A., & Wever, M. D. (2021). Automated Machine Learning, Bounded Rationality, and Rational Metareasoning. ECML/PKDD Workshop on Automating Data Science, Bilbao (Virtual).
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2021 | Conference Paper | LibreCat-ID: 27381
Damke, C., & Hüllermeier, E. (2021). Ranking Structured Objects with Graph Neural Networks. In C. Soares & L. Torgo (Eds.), Proceedings of The 24th International Conference on Discovery Science (DS 2021) (Vol. 12986, pp. 166–180). Springer. https://doi.org/10.1007/978-3-030-88942-5
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| arXiv
2021 | Conference Paper | LibreCat-ID: 21198
Hanselle, J. M., Tornede, A., Wever, M. D., & Hüllermeier, E. (2021). Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. The 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021), Delhi, India.
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2021 | Book Chapter | LibreCat-ID: 29292 |
Feldhans, R., Wilke, A., Heindorf, S., Shaker, M. H., Hammer, B., Ngonga Ngomo, A.-C., & Hüllermeier, E. (2021). Drift Detection in Text Data with Document Embeddings. In Intelligent Data Engineering and Automated Learning – IDEAL 2021. Springer International Publishing. https://doi.org/10.1007/978-3-030-91608-4_11
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2021 | Working Paper | LibreCat-ID: 45616
van Straaten, D., Melnikov, V., Hüllermeier, E., Mir Djawadi, B., & Fahr, R. (2021). Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes (Vol. 72).
LibreCat
2021 | Journal Article | LibreCat-ID: 24456 |
Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., Grimminger, A., Hammer, B., Haeb-Umbach, R., Horwath, I., Hüllermeier, E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A.-C., Schulte, C., Wachsmuth, H., Wagner, P., & Wrede, B. (2021). Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems. IEEE Transactions on Cognitive and Developmental Systems, 13(3), 717–728. https://doi.org/10.1109/tcds.2020.3044366
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2020 | Preprint | LibreCat-ID: 19603 |
Bode, H., Heid, S. H., Weber, D., Hüllermeier, E., & Wallscheid, O. (2020). Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control. ArXiv:2005.04869.
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