TY - CONF AB - In multinomial classification, reduction techniques are commonly used to decompose the original learning problem into several simpler problems. For example, by recursively bisecting the original set of classes, so-called nested dichotomies define a set of binary classification problems that are organized in the structure of a binary tree. In contrast to the existing one-shot heuristics for constructing nested dichotomies and motivated by recent work on algorithm configuration, we propose a genetic algorithm for optimizing the structure of such dichotomies. A key component of this approach is the proposed genetic representation that facilitates the application of standard genetic operators, while still supporting the exchange of partial solutions under recombination. We evaluate the approach in an extensive experimental study, showing that it yields classifiers with superior generalization performance. AU - Wever, Marcel Dominik AU - Mohr, Felix AU - Hüllermeier, Eyke ID - 2109 KW - Classification KW - Hierarchical Decomposition KW - Indirect Encoding T2 - Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018 TI - Ensembles of Evolved Nested Dichotomies for Classification ER - TY - GEN AU - Wever, Marcel Dominik AU - Mohr, Felix AU - Hüllermeier, Eyke ID - 17713 TI - Automated Multi-Label Classification based on ML-Plan ER - TY - GEN AU - Mohr, Felix AU - Wever, Marcel Dominik AU - Hüllermeier, Eyke ID - 17714 TI - Automated machine learning service composition ER - TY - GEN AU - Graf, Helena ID - 5693 TI - Ranking of Classification Algorithms in AutoML ER - TY - GEN AU - Scheibl, Manuel ID - 5936 TI - Learning about learning curves from dataset properties ER - TY - CHAP AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 6423 SN - 0302-9743 T2 - Discovery Science TI - Preference-Based Reinforcement Learning Using Dyad Ranking ER - TY - GEN ED - Abiteboul, S. ED - Arenas, M. ED - Barceló, P. ED - Bienvenu, M. ED - Calvanese, D. ED - David, C. ED - Hull, R. ED - Hüllermeier, Eyke ED - Kimelfeld, B. ED - Libkin, L. ED - Martens, W. ED - Milo, T. ED - Murlak, F. ED - Neven, F. ED - Ortiz, M. ED - Schwentick, T. ED - Stoyanovich, J. ED - Su, J. ED - Suciu, D. ED - Vianu, V. ED - Yi, K. ID - 10591 IS - 1 TI - Research Directions for Principles of Data Management VL - 7 ER - TY - CHAP AU - Couso, Ines AU - Hüllermeier, Eyke ED - Mostaghim, Sanaz ED - Nürnberger, Andreas ED - Borgelt, Christian ID - 10783 T2 - Frontiers in Computational Intelligence TI - Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators ER - TY - JOUR AU - Schäfer, D. AU - Hüllermeier, Eyke ID - 16038 IS - 5 JF - Machine Learning TI - Dyad ranking using Plackett-Luce models based on joint feature representations VL - 107 ER - TY - CONF AU - Ahmadi Fahandar, Mohsen AU - Hüllermeier, Eyke ID - 10145 T2 - Proc. 32 nd AAAI Conference on Artificial Intelligence (AAAI) TI - Learning to Rank Based on Analogical Reasoning ER - TY - CONF AU - El Mesaoudi-Paul, Adil AU - Hüllermeier, Eyke AU - Busa-Fekete, Robert ID - 10148 T2 - Proc. 35th Int. Conference on Machine Learning (ICML) TI - Ranking Distributions based on Noisy Sorting ER - TY - CONF AU - Hesse, M. AU - Timmermann, J. AU - Hüllermeier, Eyke AU - Trächtler, Ansgar ID - 10149 T2 - Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24 TI - A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart ER - TY - CHAP AU - Mencia, E.Loza AU - Fürnkranz, J. AU - Hüllermeier, Eyke AU - Rapp, M. ED - Jair Escalante, H. ED - Escalera, S. ED - Guyon, I. ED - Baro, X. ED - Güclüütürk, Y. ED - Güclü, U. ED - van Gerven, M.A.J. ID - 10152 T2 - Explainable and Interpretable Models in Computer Vision and Machine Learning TI - Learning interpretable rules for multi-label classification ER - TY - CONF AU - Nguyen, Vu-Linh AU - Destercke, Sebastian AU - Masson, M.-H. AU - Hüllermeier, Eyke ID - 10181 T2 - Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI) TI - Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty ER - TY - CONF AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 10184 T2 - Proc. 21st Int. Conference on Discovery Science (DS) TI - Preference-Based Reinforcement Learning Using Dyad Ranking ER - TY - JOUR AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 10276 IS - 5 JF - Machine Learning TI - Dyad Ranking Using Plackett-Luce Models based on joint feature representations VL - 107 ER - TY - GEN AU - Seemann, Nina AU - Geierhos, Michaela AU - Merten, Marie-Luis AU - Tophinke, Doris AU - Wever, Marcel Dominik AU - Hüllermeier, Eyke ED - Eckart, Kerstin ED - Schlechtweg, Dominik ID - 1379 T2 - Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft TI - Supporting the Cognitive Process in Annotation Tasks ER - TY - JOUR AU - Ramaswamy, Arunselvan AU - Bhatnagar, Shalabh ID - 24152 IS - 5 JF - IEEE Transactions on Automatic Control TI - Analysis of gradient descent methods with nondiminishing bounded errors VL - 63 ER - TY - JOUR AU - Ramaswamy, Arunselvan AU - Bhatnagar, Shalabh ID - 24153 IS - 3 JF - Mathematics of Operations Research TI - A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions VL - 42 ER - TY - CONF AU - Melnikov, Vitalik AU - Hüllermeier, Eyke ID - 3325 T2 - Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017 TI - Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics ER -