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: /record/2109
DOI: 10.1145/3205455.3205562

M. D. Wever, F. Mohr, and E. Hüllermeier, “Automated Multi-Label Classification based on ML-Plan.” Arxiv, 2018.
LibreCat: /record/17713

F. Mohr, M. D. Wever, and E. Hüllermeier, “Automated machine learning service composition.” 2018.
LibreCat: /record/17714

H. Graf, Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018.
LibreCat: /record/5693

M. Scheibl, Learning about learning curves from dataset properties. Universität Paderborn, 2018.
LibreCat: /record/5936

D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using Dyad Ranking,” in Discovery Science, Cham: Springer International Publishing, 2018, pp. 161–175.
LibreCat: /record/6423
DOI: 10.1007/978-3-030-01771-2_11

S. Abiteboul et al., Eds., Research Directions for Principles of Data Management, vol. 7, no. 1. 2018, pp. 1–29.
LibreCat: /record/10591

I. Couso and E. Hüllermeier, “Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators,” in Frontiers in Computational Intelligence, S. Mostaghim, A. Nürnberger, and C. Borgelt, Eds. Springer, 2018, pp. 31–46.
LibreCat: /record/10783

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: /record/16038

M. Ahmadi Fahandar and E. Hüllermeier, “Learning to Rank Based on Analogical Reasoning,” in Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI), 2018, pp. 2951–2958.
LibreCat: /record/10145