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449 Publications
2023 | Dissertation | LibreCat-ID: 45780 | 
Tornede, A. (2023). Advanced Algorithm Selection with Machine Learning: Handling Large Algorithm Sets, Learning From Censored Data, and Simplyfing Meta Level Decisions. https://doi.org/10.17619/UNIPB/1-1780
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2023 | Journal Article | LibreCat-ID: 21600
Dellnitz, M., Hüllermeier, E., Lücke, M., Ober-Blöbaum, S., Offen, C., Peitz, S., & Pfannschmidt, K. (2023). Efficient time stepping for numerical integration using reinforcement learning. SIAM Journal on Scientific Computing, 45(2), A579–A595. https://doi.org/10.1137/21M1412682
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| arXiv
2021 | Conference Paper | LibreCat-ID: 24382
Gevers, K., Schöppner, V., & Hüllermeier, E. (2021). Heated tool butt welding of two different materials – Established methods versus artificial intelligence. International Institute of Welding, online.
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 | Journal Article | LibreCat-ID: 21535
Bengs, V., Busa-Fekete, R., El Mesaoudi-Paul, A., & Hüllermeier, E. (2021). Preference-based Online Learning with Dueling Bandits: A Survey. Journal of Machine Learning Research, 22(7), 1–108.
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.
LibreCat
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: 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).
LibreCat
2021 | Conference Paper | LibreCat-ID: 22914
Mohr, F., & Wever, M. D. (2021). Replacing the Ex-Def Baseline in AutoML by Naive AutoML. 8th ICML Workshop on Automated Machine Learning, 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 | Dissertation | LibreCat-ID: 27284 |
Wever, M. D. (2021). Automated Machine Learning for Multi-Label Classification. https://doi.org/10.17619/UNIPB/1-1302
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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.
LibreCat
2020 | Book Chapter | LibreCat-ID: 19521
Pfannschmidt, K., & Hüllermeier, E. (2020). Learning Choice Functions via Pareto-Embeddings. In Lecture Notes in Computer Science. Cham. https://doi.org/10.1007/978-3-030-58285-2_30
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2020 | Conference Paper | LibreCat-ID: 19953 |
Damke, C., Melnikov, V., & Hüllermeier, E. (2020). A Novel Higher-order Weisfeiler-Lehman Graph Convolution. In S. Jialin Pan & M. Sugiyama (Eds.), Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020) (Vol. 129, pp. 49–64). Bangkok, Thailand: PMLR.
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| arXiv
2020 | Conference Paper | LibreCat-ID: 21534
Bengs, V., & Hüllermeier, E. (2020). Preselection Bandits. In International Conference on Machine Learning (pp. 778–787).
LibreCat
2020 | Preprint | LibreCat-ID: 21536
Bengs, V., & Hüllermeier, E. (2020). Multi-Armed Bandits with Censored Consumption of Resources. ArXiv:2011.00813.
LibreCat
2020 | Conference Paper | LibreCat-ID: 17407
Tornede, A., Wever, M. D., & Hüllermeier, E. (2020). Extreme Algorithm Selection with Dyadic Feature Representation. Discovery Science. Discovery Science 2020.
LibreCat
2020 | Conference Paper | LibreCat-ID: 17408
Hanselle, J. M., Tornede, A., Wever, M. D., & Hüllermeier, E. (2020). Hybrid Ranking and Regression for Algorithm Selection. KI 2020: Advances in Artificial Intelligence. 43rd German Conference on Artificial Intelligence.
LibreCat
2020 | Conference Paper | LibreCat-ID: 17424
Tornede, T., Tornede, A., Wever, M. D., Mohr, F., & Hüllermeier, E. (2020). AutoML for Predictive Maintenance: One Tool to RUL Them All. Proceedings of the ECMLPKDD 2020. IOTStream Workshop @ ECMLPKDD 2020. https://doi.org/10.1007/978-3-030-66770-2_8
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| DOI