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439 Publications
2020 | Preprint | LibreCat-ID: 20211 | 
Lienen J, Hüllermeier E. Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model. arXiv:201013118. 2020.
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2020 | Conference Paper | LibreCat-ID: 24146
Heid SH, Ramaswamy A, Hüllermeier E. Constrained Multi-Agent Optimization with Unbounded Information Delay. In: Proceedings-30. Workshop Computational Intelligence: Berlin, 26.-27. November 2020. Vol 26. ; 2020:247.
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2020 | Conference Paper | LibreCat-ID: 17407
Tornede A, Wever MD, Hüllermeier E. Extreme Algorithm Selection with Dyadic Feature Representation. In: Discovery Science. ; 2020.
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2020 | Conference Paper | LibreCat-ID: 17408
Hanselle JM, Tornede A, Wever MD, Hüllermeier E. Hybrid Ranking and Regression for Algorithm Selection. In: KI 2020: Advances in Artificial Intelligence. ; 2020.
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2020 | Conference Paper | LibreCat-ID: 17424
Tornede T, Tornede A, Wever MD, Mohr F, Hüllermeier E. AutoML for Predictive Maintenance: One Tool to RUL Them All. In: Proceedings of the ECMLPKDD 2020. ; 2020. doi:10.1007/978-3-030-66770-2_8
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2020 | Preprint | LibreCat-ID: 17605 |
Heid SH, Wever MD, Hüllermeier E. Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction. Journal of Data Mining and Digital Humanities.
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2020 | Conference Paper | LibreCat-ID: 20306
Tornede A, Wever MD, Hüllermeier E. Towards Meta-Algorithm Selection. In: Workshop MetaLearn 2020 @ NeurIPS 2020. ; 2020.
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2020 | Book Chapter | LibreCat-ID: 18014
El Mesaoudi-Paul A, Weiß D, Bengs V, Hüllermeier E, Tierney K. Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach. In: Learning and Intelligent Optimization. LION 2020. Vol 12096. Lecture Notes in Computer Science. Cham: Springer; 2020:216-232. doi:10.1007/978-3-030-53552-0_22
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2020 | Preprint | LibreCat-ID: 18017
El Mesaoudi-Paul A, Bengs V, Hüllermeier E. Online Preselection with Context Information under the Plackett-Luce Model. arXiv:200204275.
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2020 | Conference Paper | LibreCat-ID: 18276
Tornede A, Wever MD, Werner S, Mohr F, Hüllermeier E. Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. In: ACML 2020. ; 2020.
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2020 | Journal Article | LibreCat-ID: 16725
Richter C, Hüllermeier E, Jakobs M-C, Wehrheim H. Algorithm Selection for Software Validation Based on Graph Kernels. Journal of Automated Software Engineering.
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2020 | Conference Paper | LibreCat-ID: 15629
Wever MD, Tornede A, Mohr F, Hüllermeier E. LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification. In: Springer.
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2019 | Conference Abstract | LibreCat-ID: 8868
Wever MD, Mohr F, Hüllermeier E, Hetzer A. Towards Automated Machine Learning for Multi-Label Classification. In: ; 2019.
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2019 | Journal Article | LibreCat-ID: 10578
Tagne VK, Fotso S, Fono LA, Hüllermeier E. Choice Functions Generated by Mallows and Plackett–Luce Relations. New Mathematics and Natural Computation. 2019;15(2):191-213.
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2019 | Journal Article | LibreCat-ID: 15001
Couso I, Borgelt C, Hüllermeier E, Kruse R. Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning. IEEE Computational Intelligence Magazine. 2019:31-44. doi:10.1109/mci.2018.2881642
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2019 | Journal Article | LibreCat-ID: 15002 |
Waegeman W, Dembczynski K, Hüllermeier E. Multi-target prediction: a unifying view on problems and methods. Data Mining and Knowledge Discovery. 2019;33(2):293-324. doi:10.1007/s10618-018-0595-5
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2019 | Conference Paper | LibreCat-ID: 15003
Mortier T, Wydmuch M, Dembczynski K, Hüllermeier E, Waegeman W. 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. ; 2019.
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2019 | Book Chapter | LibreCat-ID: 15004
Ahmadi Fahandar M, Hüllermeier E. Feature Selection for Analogy-Based Learning to Rank. In: Discovery Science. Cham; 2019. doi:10.1007/978-3-030-33778-0_22
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2019 | Book Chapter | LibreCat-ID: 15005
Ahmadi Fahandar M, Hüllermeier E. Analogy-Based Preference Learning with Kernels. In: KI 2019: Advances in Artificial Intelligence. Cham; 2019. doi:10.1007/978-3-030-30179-8_3
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2019 | Book Chapter | LibreCat-ID: 15006
Nguyen V-L, Destercke S, Hüllermeier E. Epistemic Uncertainty Sampling. In: Discovery Science. Cham; 2019. doi:10.1007/978-3-030-33778-0_7
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