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448 Publications


2019 | Conference Paper | LibreCat-ID: 15011 | OA
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 Paper | LibreCat-ID: 15013
Brinker K, Hüllermeier E. A Reduction of Label Ranking to Multiclass Classification. In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases. Würzburg, Germany; 2019.
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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 | Journal Article | LibreCat-ID: 15015
Henzgen S, Hüllermeier E. Mining Rank Data. ACM Transactions on Knowledge Discovery from Data. 2019:1-36. doi:10.1145/3363572
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2019 | Journal Article | LibreCat-ID: 14027
Bengs V, Eulert M, Holzmann H. Asymptotic confidence sets for the jump curve in bivariate regression problems. Journal of Multivariate Analysis. 2019:291-312. doi:10.1016/j.jmva.2019.02.017
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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 | 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 | OA
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 | OA
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 | Preprint | LibreCat-ID: 19524
Pfannschmidt K, Gupta P, Hüllermeier E. Deep Architectures for Learning Context-dependent Ranking Functions. arXiv:180305796. 2018.
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