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Online Learning with Feedback Graphs: Beyond Bandits., , , и . COLT, том 40 из JMLR Workshop and Conference Proceedings, стр. 23-35. JMLR.org, (2015)Bandits with switching costs: T2/3 regret., , , и . STOC, стр. 459-467. ACM, (2014)Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime., , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 1107-1120. PMLR, (2023)Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions., , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 5969-5978. PMLR, (2021)Robust Bi-Tempered Logistic Loss Based on Bregman Divergences., , , и . NeurIPS, стр. 14987-14996. (2019)Fast Rates for Exp-concave Empirical Risk Minimization., и . NIPS, стр. 1477-1485. (2015)Distributed Exploration in Multi-Armed Bandits., , , , и . NIPS, стр. 854-862. (2013)The Blinded Bandit: Learning with Adaptive Feedback., , и . NIPS, стр. 1610-1618. (2014)Never Go Full Batch (in Stochastic Convex Optimization)., , , и . NeurIPS, стр. 25033-25043. (2021)Better Best of Both Worlds Bounds for Bandits with Switching Costs., , , и . NeurIPS, (2022)