Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
2018 | Preprint | LibreCat-ID: 19524
K. Pfannschmidt, P. Gupta, and E. Hüllermeier, “Deep Architectures for Learning Context-dependent Ranking Functions,” arXiv:1803.05796. 2018.LibreCat
2018 | Bachelorsthesis | LibreCat-ID: 5936
M. Scheibl, Learning about learning curves from dataset properties. Universität Paderborn, 2018.LibreCat
2018 | Conference Paper | LibreCat-ID: 10148
A. El Mesaoudi-Paul, E. Hüllermeier, and R. Busa-Fekete, “Ranking Distributions based on Noisy Sorting,” in Proc. 35th Int. Conference on Machine Learning (ICML), 2018, pp. 3469–3477.LibreCat
2018 | Conference Paper | LibreCat-ID: 10181
V.-L. Nguyen, S. Destercke, M.-H. Masson, and E. Hüllermeier, “Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty,” in Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 2018, pp. 5089–5095.LibreCat
2018 | Journal Article | LibreCat-ID: 16038
D. Schäfer and E. Hüllermeier, “Dyad ranking using Plackett-Luce models based on joint feature representations,” Machine Learning, vol. 107, no. 5, pp. 903–941, 2018.LibreCat
2018 | Conference Paper | LibreCat-ID: 2109
M. D. Wever, F. Mohr, and E. Hüllermeier, “Ensembles of Evolved Nested Dichotomies for Classification,” in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, Kyoto, Japan, 2018.LibreCat | Files available | DOI | Download (ext.)