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448 Publications
2018 | Conference Paper | LibreCat-ID: 10181
Nguyen, V.-L., Destercke, S., Masson, M.-H., & Hüllermeier, E. (2018). Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 5089–5095.
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2018 | Conference Paper | LibreCat-ID: 10184
Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement Learning Using Dyad Ranking. Proc. 21st Int. Conference on Discovery Science (DS), 161–175.
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2018 | Journal Article | LibreCat-ID: 10276
Schäfer, D., & Hüllermeier, E. (2018). Dyad Ranking Using Plackett-Luce Models based on joint feature representations. Machine Learning, 107(5), 903–941.
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2018 | Conference Abstract | LibreCat-ID: 1379 | 
Seemann, N., Geierhos, M., Merten, M.-L., Tophinke, D., Wever, M. D., & Hüllermeier, E. (2018). Supporting the Cognitive Process in Annotation Tasks. In K. Eckart & D. Schlechtweg (Eds.), Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft.
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2018 | Journal Article | LibreCat-ID: 22996
Hesse, M., Timmermann, J., Hüllermeier, E., & Trächtler, A. (2018). A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart. Procedia Manufacturing, 24, 15–20.
LibreCat
2017 | Conference Paper | LibreCat-ID: 3325
Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing. https://doi.org/10.5445/KSP/1000074341
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2017 | Conference Paper | LibreCat-ID: 71
Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting Rankings of Software Verification Tools. In Proceedings of the 3rd International Workshop on Software Analytics (pp. 23–26). https://doi.org/10.1145/3121257.3121262
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2017 | Report | LibreCat-ID: 72
Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting Rankings of Software Verification Competitions.
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2017 | Encyclopedia Article | LibreCat-ID: 10589
Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In Encyclopedia of Machine Learning and Data Mining (pp. 1000–1005).
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2017 | Book Chapter | LibreCat-ID: 10784
Fürnkranz, J., & Hüllermeier, E. (2017). Preference Learning. In C. Sammut & G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining (Vol. 107, pp. 1000–1005). Springer.
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2017 | Conference Paper | LibreCat-ID: 1180 |
Wever, M. D., Mohr, F., & Hüllermeier, E. (2017). Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization. In 27th Workshop Computational Intelligence. Dortmund.
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2017 | Conference Paper | LibreCat-ID: 15397
Melnikov, V., & Hüllermeier, E. (2017). Optimizing the structure of nested dichotomies. A comparison of two heuristics. In F. Hoffmann, E. Hüllermeier, & R. Mikut (Eds.), in Proceedings 27th Workshop Computational Intelligence, Dortmund Germany (pp. 1–12). KIT Scientific Publishing.
LibreCat
2017 | Conference Paper | LibreCat-ID: 15399
Czech, M., Hüllermeier, E., Jacobs, M. C., & Wehrheim, H. (2017). Predicting rankings of software verification tools. In in Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany.
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2017 | Conference Paper | LibreCat-ID: 15110
Couso, I., Dubois, D., & Hüllermeier, E. (2017). Maximum likelihood estimation and coarse data. In in Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain (pp. 3–16). Springer.
LibreCat
2017 | Conference Paper | LibreCat-ID: 10204
Ewerth, R., Springstein, M., Müller, E., Balz, A., Gehlhaar, J., Naziyok, T., … Hüllermeier, E. (2017). Estimating relative depth in single images via rankboost. In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017) (pp. 919–924).
LibreCat
2017 | Conference Paper | LibreCat-ID: 10205
Ahmadi Fahandar, M., Hüllermeier, E., & Couso, I. (2017). Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening. In Proc. 34th Int. Conf. on Machine Learning (ICML 2017) (pp. 1078–1087).
LibreCat
2017 | Conference Paper | LibreCat-ID: 10206 |
Mohr, F., Lettmann, T., & Hüllermeier, E. (2017). Planning with Independent Task Networks. In Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017) (pp. 193–206). https://doi.org/10.1007/978-3-319-67190-1_15
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2017 | Conference Paper | LibreCat-ID: 10207
Czech, M., Hüllermeier, E., Jakobs, M.-C., & Wehrheim, H. (2017). Predicting rankings of software verification tools. In Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017 (pp. 23–26).
LibreCat
2017 | Conference Paper | LibreCat-ID: 10208
Couso, I., Dubois, D., & Hüllermeier, E. (2017). Maximum Likelihood Estimation and Coarse Data. In Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017) (pp. 3–16).
LibreCat
2017 | Conference Paper | LibreCat-ID: 10209
Ahmadi Fahandar, M., & Hüllermeier, E. (2017). Learning to Rank based on Analogical Reasoning. In Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence.
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