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429 Publications


2019 | Conference Paper | LibreCat-ID: 15003
T. Mortier, M. Wydmuch, K. Dembczynski, E. Hüllermeier, and W. Waegeman, “Set-Valued Prediction in Multi-Class Classification,” in 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.
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2019 | Journal Article | LibreCat-ID: 15015
S. Henzgen and E. Hüllermeier, “Mining Rank Data,” ACM Transactions on Knowledge Discovery from Data, pp. 1–36, 2019.
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2019 | Conference Paper | LibreCat-ID: 10232
M. D. Wever, F. Mohr, A. Tornede, and E. Hüllermeier, “Automating Multi-Label Classification Extending ML-Plan,” presented at the 6th ICML Workshop on Automated Machine Learning (AutoML 2019), Long Beach, CA, USA, 2019.
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2019 | Journal Article | LibreCat-ID: 10578
V. K. Tagne, S. Fotso, L. A. Fono, and E. Hüllermeier, “Choice Functions Generated by Mallows and Plackett–Luce Relations,” New Mathematics and Natural Computation, vol. 15, no. 2, pp. 191–213, 2019.
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2019 | Book Chapter | LibreCat-ID: 15004
M. Ahmadi Fahandar and E. Hüllermeier, “Feature Selection for Analogy-Based Learning to Rank,” in Discovery Science, Cham, 2019.
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2019 | Conference Paper | LibreCat-ID: 15009
N. Epple, S. Dari, L. Drees, V. Protschky, and A. Riener, “Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries,” in 2019 IEEE Intelligent Vehicles Symposium (IV), 2019.
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2019 | Conference Paper | LibreCat-ID: 15011
A. Tornede, M. D. Wever, and E. Hüllermeier, “Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking,” in Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, Dortmund, 2019, pp. 135–146.
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2019 | Book Chapter | LibreCat-ID: 15005
M. Ahmadi Fahandar and E. Hüllermeier, “Analogy-Based Preference Learning with Kernels,” in KI 2019: Advances in Artificial Intelligence, Cham, 2019.
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2019 | Preprint | LibreCat-ID: 18016
V. Bengs and E. Hüllermeier, “Preselection Bandits under the Plackett-Luce Model,” arXiv:1907.06123. .
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2019 | Conference Abstract | LibreCat-ID: 13132
F. Mohr, M. D. Wever, A. Tornede, and E. Hüllermeier, “From Automated to On-The-Fly Machine Learning,” in INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, Kassel, 2019, pp. 273–274.
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2019 | Journal Article | LibreCat-ID: 14027
V. Bengs, M. Eulert, and H. Holzmann, “Asymptotic confidence sets for the jump curve in bivariate regression problems,” Journal of Multivariate Analysis, pp. 291–312, 2019.
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2019 | Journal Article | LibreCat-ID: 15001
I. Couso, C. Borgelt, E. Hüllermeier, and R. Kruse, “Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning,” IEEE Computational Intelligence Magazine, pp. 31–44, 2019.
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2019 | Book Chapter | LibreCat-ID: 15006
V.-L. Nguyen, S. Destercke, and E. Hüllermeier, “Epistemic Uncertainty Sampling,” in Discovery Science, Cham, 2019.
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2019 | Conference Paper | LibreCat-ID: 15013
K. Brinker and E. Hüllermeier, “A Reduction of Label Ranking to Multiclass Classification,” in Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, 2019.
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2019 | Conference Abstract | LibreCat-ID: 8868
M. D. Wever, F. Mohr, E. Hüllermeier, and A. Hetzer, “Towards Automated Machine Learning for Multi-Label Classification,” presented at the European Conference on Data Analytics (ECDA), Bayreuth, Germany, 2019.
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2019 | Journal Article | LibreCat-ID: 15025
M. D. Wever, L. van Rooijen, and H. Hamann, “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets,” Evolutionary Computation.
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2018 | Conference Paper | LibreCat-ID: 10184
D. Schäfer and E. Hüllermeier, “Preference-Based Reinforcement Learning Using Dyad Ranking,” in Proc. 21st Int. Conference on Discovery Science (DS), 2018, pp. 161–175.
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2018 | Conference Paper | LibreCat-ID: 2479
F. Mohr, M. D. Wever, E. Hüllermeier, and A. Faez, “(WIP) Towards the Automated Composition of Machine Learning Services,” in SCC, San Francisco, CA, USA, 2018.
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2018 | Conference Paper | LibreCat-ID: 3852
M. D. Wever, F. Mohr, and E. Hüllermeier, “ML-Plan for Unlimited-Length Machine Learning Pipelines,” in ICML 2018 AutoML Workshop, Stockholm, Sweden, 2018.
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2018 | Conference (Editor) | LibreCat-ID: 10591
S. Abiteboul et al., Eds., Research Directions for Principles of Data Management, vol. 7, no. 1. 2018, pp. 1–29.
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