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449 Publications
2019 | Preprint | LibreCat-ID: 18018
Bengs, Viktor, and Hajo Holzmann. “Uniform Approximation in Classical Weak Convergence Theory.” ArXiv:1903.09864, 2019.
LibreCat
2019 | Conference Abstract | LibreCat-ID: 8868
Wever, Marcel Dominik, et al. Towards Automated Machine Learning for Multi-Label Classification. 2019.
LibreCat
| Files available
2019 | Journal Article | LibreCat-ID: 10578
Tagne, V. K., et al. “Choice Functions Generated by Mallows and Plackett–Luce Relations.” New Mathematics and Natural Computation, vol. 15, no. 2, 2019, pp. 191–213.
LibreCat
2019 | Journal Article | LibreCat-ID: 15001
Couso, Ines, et al. “Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning.” IEEE Computational Intelligence Magazine, 2019, pp. 31–44, doi:10.1109/mci.2018.2881642.
LibreCat
| DOI
2019 | Journal Article | LibreCat-ID: 15002 | 
Waegeman, Willem, et al. “Multi-Target Prediction: A Unifying View on Problems and Methods.” Data Mining and Knowledge Discovery, vol. 33, no. 2, 2019, pp. 293–324, doi:10.1007/s10618-018-0595-5.
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2019 | Conference Paper | LibreCat-ID: 15003
Mortier, Thomas, et al. “Set-Valued Prediction in Multi-Class Classification.” 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.
LibreCat
2019 | Book Chapter | LibreCat-ID: 15004
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Feature Selection for Analogy-Based Learning to Rank.” Discovery Science, 2019, doi:10.1007/978-3-030-33778-0_22.
LibreCat
| DOI
2019 | Book Chapter | LibreCat-ID: 15005
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Analogy-Based Preference Learning with Kernels.” KI 2019: Advances in Artificial Intelligence, 2019, doi:10.1007/978-3-030-30179-8_3.
LibreCat
| DOI
2019 | Book Chapter | LibreCat-ID: 15006
Nguyen, Vu-Linh, et al. “Epistemic Uncertainty Sampling.” Discovery Science, 2019, doi:10.1007/978-3-030-33778-0_7.
LibreCat
| DOI
2019 | Conference Paper | LibreCat-ID: 15007 |
Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA.” 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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| DOI