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38 Publications
2021 | Dissertation | LibreCat-ID: 27284 | 
Wever MD. Automated Machine Learning for Multi-Label Classification.; 2021. doi:10.17619/UNIPB/1-1302
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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. Published online 2021.
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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 | 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 | 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 | Journal Article | LibreCat-ID: 15025
Wever MD, van Rooijen L, Hamann H. Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary Computation. 2020;28(2):165–193. doi:10.1162/evco_a_00266
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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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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 | Conference Paper | LibreCat-ID: 15011 |
Tornede A, Wever MD, Hüllermeier E. Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking. In: Hoffmann F, Hüllermeier E, Mikut R, eds. Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019. KIT Scientific Publishing, Karlsruhe; 2019:135-146.
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2019 | Conference Abstract | LibreCat-ID: 13132
Mohr F, Wever MD, Tornede A, Hüllermeier E. From Automated to On-The-Fly Machine Learning. In: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft. INFORMATIK 2019, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik. Bonn: Gesellschaft für Informatik e.V.; 2019:273-274.
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2019 | Conference Paper | LibreCat-ID: 10232 |
Wever MD, Mohr F, Tornede A, Hüllermeier E. Automating Multi-Label Classification Extending ML-Plan. In: ; 2019.
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2018 | Conference Paper | LibreCat-ID: 2479 |
Mohr F, Wever MD, Hüllermeier E, Faez A. (WIP) Towards the Automated Composition of Machine Learning Services. In: SCC. San Francisco, CA, USA: IEEE; 2018. doi:10.1109/SCC.2018.00039
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2018 | Conference Paper | LibreCat-ID: 2857 |
Mohr F, Lettmann T, Hüllermeier E, Wever MD. Programmatic Task Network Planning. In: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning. AAAI; 2018:31-39.
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2018 | Conference Paper | LibreCat-ID: 2471 |
Mohr F, Wever MD, Hüllermeier E. On-The-Fly Service Construction with Prototypes. In: SCC. San Francisco, CA, USA: IEEE Computer Society; 2018. doi:10.1109/SCC.2018.00036
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2018 | Journal Article | LibreCat-ID: 3510 |
Mohr F, Wever MD, Hüllermeier E. ML-Plan: Automated Machine Learning via Hierarchical Planning. Machine Learning. Published online 2018:1495-1515. doi:10.1007/s10994-018-5735-z
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2018 | Conference Paper | LibreCat-ID: 3552 |
Mohr F, Wever MD, Hüllermeier E. Reduction Stumps for Multi-Class Classification. In: Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch, the Netherlands. doi:10.1007/978-3-030-01768-2_19
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