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443 Publications
2022 | Journal Article | LibreCat-ID: 33090
Gevers K, Tornede A, Wever MD, Schöppner V, Hüllermeier E. A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials. Welding in the World. Published online 2022. doi:10.1007/s40194-022-01339-9
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2022 | Report | LibreCat-ID: 36227
Hammer B, Hüllermeier E, Lohweg V, 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 M, Fumagalli F, Hammer B, Huellermeier E. Agnostic Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz. 2022;36(3-4):211-224. doi:10.1007/s13218-022-00766-6
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| DOI
2021 | Journal Article | LibreCat-ID: 24143
Drees JP, Gupta P, Hüllermeier E, et al. Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs! 14th ACM Workshop on Artificial Intelligence and Security. Published online 2021.
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2021 | Journal Article | LibreCat-ID: 24148
Ramaswamy A, Hüllermeier E. Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis. IEEE Transactions on Artificial Intelligence (to appear). Published online 2021.
LibreCat
2021 | Journal Article | LibreCat-ID: 21004
Wever MD, Tornede A, Mohr F, Hüllermeier E. AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Published online 2021:1-1. doi:10.1109/tpami.2021.3051276
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2021 | Journal Article | LibreCat-ID: 21092
Mohr F, Wever MD, Tornede A, Hüllermeier E. Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence.
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2021 | Conference Paper | LibreCat-ID: 21570
Tornede T, Tornede A, Wever MD, Hüllermeier E. Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance. In: Proceedings of the Genetic and Evolutionary Computation Conference. ; 2021.
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2021 | Journal Article | LibreCat-ID: 21636
Lienen J, Hüllermeier E. Instance weighting through data imprecisiation. International Journal of Approximate Reasoning. 2021.
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2021 | Conference Paper | LibreCat-ID: 21637 | 
Lienen J, Hüllermeier E. From Label Smoothing to Label Relaxation. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI. Vol 35. AAAI Press; 2021:8583-8591.
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2021 | Conference Paper | LibreCat-ID: 23779
Bernijazov R, Dicks A, Dumitrescu R, et al. A Meta-Review on Artificial Intelligence in Product Creation. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21). ; 2021.
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2021 | Conference Paper | LibreCat-ID: 22280
Lienen J, Hüllermeier E, Ewerth R, Nommensen N. Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR. ; 2021:14595-14604.
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2021 | Preprint | LibreCat-ID: 22509 |
Lienen J, Hüllermeier E. Credal Self-Supervised Learning. arXiv:210611853. 2021.
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2021 | Conference Paper | LibreCat-ID: 22913
Hüllermeier E, Mohr F, Tornede A, Wever MD. Automated Machine Learning, Bounded Rationality, and Rational Metareasoning. In: ; 2021.
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2021 | Conference Paper | LibreCat-ID: 27381
Damke C, Hüllermeier E. Ranking Structured Objects with Graph Neural Networks. In: Soares C, Torgo L, eds. Proceedings of The 24th International Conference on Discovery Science (DS 2021). Vol 12986. Lecture Notes in Computer Science. Springer; 2021:166-180. doi:10.1007/978-3-030-88942-5
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| DOI
| arXiv
2021 | Conference Paper | LibreCat-ID: 21198
Hanselle JM, Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. Published online 2021.
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2021 | Book Chapter | LibreCat-ID: 29292 |
Feldhans R, Wilke A, Heindorf S, et al. Drift Detection in Text Data with Document Embeddings. In: Intelligent Data Engineering and Automated Learning – IDEAL 2021. Springer International Publishing; 2021. doi:10.1007/978-3-030-91608-4_11
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