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428 Publications


2018 | Preprint | LibreCat-ID: 19524
Pfannschmidt, Karlson, Pritha Gupta, and Eyke Hüllermeier. “Deep Architectures for Learning Context-Dependent Ranking Functions.” ArXiv:1803.05796, 2018.
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2018 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. Universität Paderborn, 2018.
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2018 | Conference Paper | LibreCat-ID: 10148
El Mesaoudi-Paul, Adil, Eyke Hüllermeier, and Robert Busa-Fekete. “Ranking Distributions Based on  Noisy Sorting.” In Proc. 35th Int. Conference on Machine Learning (ICML), 3469–77, 2018.
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2018 | Conference Paper | LibreCat-ID: 10181
Nguyen, Vu-Linh, Sebastian Destercke, M.-H. Masson, and Eyke Hüllermeier. “Reliable Multi-Class Classification Based on Pairwise Epistemic and Aleatoric Uncertainty.” In Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 5089–95, 2018.
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2018 | Journal Article | LibreCat-ID: 16038
Schäfer, D., and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning 107, no. 5 (2018): 903–41.
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2018 | Conference Paper | LibreCat-ID: 2109
Wever, Marcel Dominik, Felix Mohr, and Eyke 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: ACM, 2018. https://doi.org/10.1145/3205455.3205562.
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2018 | Conference Paper | LibreCat-ID: 2471
Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “On-The-Fly Service Construction with Prototypes.” In SCC. San Francisco, CA, USA: IEEE Computer Society, 2018. https://doi.org/10.1109/SCC.2018.00036.
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2018 | Book Chapter | LibreCat-ID: 6423
Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” In Discovery Science, 161–75. Cham: Springer International Publishing, 2018. https://doi.org/10.1007/978-3-030-01771-2_11.
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2018 | Preprint | LibreCat-ID: 17714
Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Automated Machine Learning Service Composition,” 2018.
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2018 | Journal Article | LibreCat-ID: 10276
Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning 107, no. 5 (2018): 903–41.
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2018 | Conference Paper | LibreCat-ID: 10149
Hesse, M., J. Timmermann, Eyke Hüllermeier, and Ansgar Trächtler. “A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.” In Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 15–20, 2018.
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2018 | Book Chapter | LibreCat-ID: 10783
Couso, Ines, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Frontiers in Computational Intelligence, edited by Sanaz Mostaghim, Andreas Nürnberger, and Christian Borgelt, 31–46. Springer, 2018.
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2018 | Conference Paper | LibreCat-ID: 2857
Mohr, Felix, Theodor Lettmann, Eyke Hüllermeier, and Marcel Dominik Wever. “Programmatic Task Network Planning.” In Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, 31–39. AAAI, 2018.
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2018 | Conference Paper | LibreCat-ID: 3552
Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Reduction Stumps for Multi-Class Classification.” In Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch, the Netherlands, n.d. https://doi.org/10.1007/978-3-030-01768-2_19.
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2018 | Conference Paper | LibreCat-ID: 10145
Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” In Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2951–58, 2018.
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2018 | Book Chapter | LibreCat-ID: 10152
Mencia, E.Loza, J. Fürnkranz, Eyke Hüllermeier, and M. Rapp. “Learning Interpretable Rules for Multi-Label Classification.” In Explainable and Interpretable Models in Computer Vision and Machine Learning, edited by H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M.A.J. van Gerven, 81–113. The Springer Series on Challenges in Machine Learning. Springer, 2018.
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2018 | Conference Abstract | LibreCat-ID: 1379
Seemann, Nina, Michaela Geierhos, Marie-Luis Merten, Doris Tophinke, Marcel Dominik Wever, and Eyke Hüllermeier. “Supporting the Cognitive Process in Annotation Tasks.” In Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, edited by Kerstin Eckart and Dominik Schlechtweg, 2018.
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2018 | Journal Article | LibreCat-ID: 3510
Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “ML-Plan: Automated Machine Learning via Hierarchical Planning.” Machine Learning, 2018, 1495–1515. https://doi.org/10.1007/s10994-018-5735-z.
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2018 | Bachelorsthesis | LibreCat-ID: 5693
Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018.
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2018 | Journal Article | LibreCat-ID: 3402
Melnikov, Vitalik, and Eyke Hüllermeier. “On the Effectiveness of Heuristics for Learning Nested Dichotomies: An Empirical Analysis.” Machine Learning, 2018. https://doi.org/10.1007/s10994-018-5733-1.
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