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Adaptation Algorithm and Theory Based on Generalized Discrepancy., , и . KDD, стр. 169-178. ACM, (2015)Invited talk: Can learning kernels help performance?. ICML, том 382 из ACM International Conference Proceeding Series, стр. 1. ACM, (2009)Online Learning with Abstention., , , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 1067-1075. PMLR, (2018)Support-vector networks, и . Machine learning, 20 (3): 273--297 (1995)Margin-Based Ranking Meets Boosting in the Middle., , , и . COLT, том 3559 из Lecture Notes in Computer Science, стр. 63-78. Springer, (2005)Structural Maxent Models., , , и . ICML, том 37 из JMLR Workshop and Conference Proceedings, стр. 391-399. JMLR.org, (2015)On-Line Learning Algorithms for Path Experts with Non-Additive Losses., , , и . COLT, том 40 из JMLR Workshop and Conference Proceedings, стр. 424-447. JMLR.org, (2015)Efficient Computation of the Relative Entropy of Probabilistic Automata., , , и . LATIN, том 3887 из Lecture Notes in Computer Science, стр. 323-336. Springer, (2006)Domain Adaptation in Regression., и . ALT, том 6925 из Lecture Notes in Computer Science, стр. 308-323. Springer, (2011)Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses., , , , и . NeurIPS, стр. 6811-6822. (2018)