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A scaled Bregman theorem with applications., , и . NIPS, стр. 19-27. (2016)Contextual Gaussian Process Bandit Optimization., и . NIPS, стр. 2447-2455. (2011)Cell density in prostate histopathology images as a measure of tumor distribution., , , , , , , и . Medical Imaging: Digital Pathology, том 9041 из SPIE Proceedings, стр. 90410S. SPIE, (2014)Revisiting revisits in trajectory recommendation., , , и . CitRec@RecSys, стр. 2:1-2:6. ACM, (2017)Part & Clamp: Efficient Structured Output Learning., и . AISTATS, том 22 из JMLR Proceedings, стр. 877-885. JMLR.org, (2012)Linking losses for density ratio and class-probability estimation., и . ICML, том 48 из JMLR Workshop and Conference Proceedings, стр. 304-313. JMLR.org, (2016)An Automated Combination of Kernels for Predicting Protein Subcellular Localization., и . WABI, том 5251 из Lecture Notes in Computer Science, стр. 186-197. Springer, (2008)Stochastic gradient updates yield deep equilibrium kernels., и . Trans. Mach. Learn. Res., (2023)Quantile Bandits for Best Arms Identification., и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 12513-12523. PMLR, (2021)Learning SVM in Kreĭn Spaces., , и . IEEE Trans. Pattern Anal. Mach. Intell., 38 (6): 1204-1216 (2016)