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431 Publications


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. 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: 21198
Hanselle JM, Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. In: ; 2021.
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2020 | Conference Paper | LibreCat-ID: 19953
Damke C, Melnikov V, Hüllermeier E. A Novel Higher-order Weisfeiler-Lehman Graph Convolution. In: Jialin Pan S, Sugiyama M, eds. Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020). Vol 129. Proceedings of Machine Learning Research. Bangkok, Thailand: PMLR; 2020:49-64.
LibreCat | Files available | arXiv
 

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 | 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: 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: 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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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: 19521
Pfannschmidt K, Hüllermeier E. Learning Choice Functions via Pareto-Embeddings. In: Lecture Notes in Computer Science. Cham; 2020. doi:10.1007/978-3-030-58285-2_30
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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 | 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 | 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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2019 | Journal Article | LibreCat-ID: 14028
Bengs V, Holzmann H. Adaptive confidence sets for kink estimation. Electronic Journal of Statistics. 2019:1523-1579. doi:10.1214/19-ejs1555
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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: 15014
Hüllermeier E, Couso I, Diestercke S. Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants. In: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management. ; 2019.
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2019 | Conference Paper | LibreCat-ID: 15007
Melnikov V, Hüllermeier E. Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA. In: Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101). ; 2019. doi:10.1016/j.jmva.2019.02.017
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2019 | Journal Article | LibreCat-ID: 17565
Merten M-L, Seemann N, Wever MD. Grammatikwandel digital-kulturwissenschaftlich erforscht. Mittelniederdeutscher Sprachausbau im interdisziplinären Zugriff. Niederdeutsches Jahrbuch. 2019;(142):124-146.
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