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440 Publications
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 | Preprint | LibreCat-ID: 20211 |
Lienen, J., & Hüllermeier, E. (2020). Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model. ArXiv:2010.13118.
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2020 | Conference Paper | LibreCat-ID: 24146
Heid, S. H., Ramaswamy, A., & Hüllermeier, E. (2020). Constrained Multi-Agent Optimization with Unbounded Information Delay. Proceedings-30. Workshop Computational Intelligence: Berlin, 26.-27. November 2020, 26, 247.
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
2020 | Preprint | LibreCat-ID: 17605 |
Heid, S. H., Wever, M. D., & Hüllermeier, E. (n.d.). Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction. In Journal of Data Mining and Digital Humanities. episciences.
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2020 | Conference Paper | LibreCat-ID: 20306
Tornede, A., Wever, M. D., & Hüllermeier, E. (2020). Towards Meta-Algorithm Selection. Workshop MetaLearn 2020 @ NeurIPS 2020. Workshop MetaLearn 2020 @ NeurIPS 2020, Online.
LibreCat
2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul, A., Weiß, D., Bengs, V., Hüllermeier, E., & Tierney, K. (2020). Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. In Learning and Intelligent Optimization. LION 2020. (Vol. 12096, pp. 216–232). Cham: Springer. https://doi.org/10.1007/978-3-030-53552-0_22
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| DOI
2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul, A., Bengs, V., & Hüllermeier, E. (n.d.). Online Preselection with Context Information under the Plackett-Luce Model. ArXiv:2002.04275.
LibreCat
2020 | Conference Paper | LibreCat-ID: 18276
Tornede, A., Wever, M. D., Werner, S., Mohr, F., & Hüllermeier, E. (2020). Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. ACML 2020. 12th Asian Conference on Machine Learning, Bangkok, Thailand.
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2020 | Journal Article | LibreCat-ID: 16725
Richter, C., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (n.d.). Algorithm Selection for Software Validation Based on Graph Kernels. Journal of Automated Software Engineering.
LibreCat
2020 | Conference Paper | LibreCat-ID: 15629
Wever, M. D., Tornede, A., Mohr, F., & Hüllermeier, E. (n.d.). LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification. Symposium on Intelligent Data Analysis, Konstanz, Germany.
LibreCat
2019 | Conference Abstract | LibreCat-ID: 8868
Wever, M. D., Mohr, F., Hüllermeier, E., & Hetzer, A. (2019). Towards Automated Machine Learning for Multi-Label Classification. Presented at the European Conference on Data Analytics (ECDA), Bayreuth, Germany.
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2019 | Journal Article | LibreCat-ID: 10578
Tagne, V. K., Fotso, S., Fono, L. A., & Hüllermeier, E. (2019). Choice Functions Generated by Mallows and Plackett–Luce Relations. New Mathematics and Natural Computation, 15(2), 191–213.
LibreCat
2019 | Journal Article | LibreCat-ID: 15001
Couso, I., Borgelt, C., Hüllermeier, E., & Kruse, R. (2019). Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning. IEEE Computational Intelligence Magazine, 31–44. https://doi.org/10.1109/mci.2018.2881642
LibreCat
| DOI
2019 | Journal Article | LibreCat-ID: 15002 |
Waegeman, W., Dembczynski, K., & Hüllermeier, E. (2019). Multi-target prediction: a unifying view on problems and methods. Data Mining and Knowledge Discovery, 33(2), 293–324. https://doi.org/10.1007/s10618-018-0595-5
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| DOI
2019 | Conference Paper | LibreCat-ID: 15003
Mortier, T., Wydmuch, M., Dembczynski, K., Hüllermeier, E., & Waegeman, W. (2019). Set-Valued Prediction in Multi-Class Classification. In Proceedings of the 31st Benelux Conference on Artificial Intelligence {(BNAIC} 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019.
LibreCat
2019 | Book Chapter | LibreCat-ID: 15004
Ahmadi Fahandar, M., & Hüllermeier, E. (2019). Feature Selection for Analogy-Based Learning to Rank. In Discovery Science. Cham. https://doi.org/10.1007/978-3-030-33778-0_22
LibreCat
| DOI
2019 | Book Chapter | LibreCat-ID: 15005
Ahmadi Fahandar, M., & Hüllermeier, E. (2019). Analogy-Based Preference Learning with Kernels. In KI 2019: Advances in Artificial Intelligence. Cham. https://doi.org/10.1007/978-3-030-30179-8_3
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| DOI