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Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret., , and . ICML, icml.cc / Omnipress, (2012)Online Learning with a Hint., , , and . NIPS, page 5299-5308. (2017)Incentive Compatible Regression Learning., , and . Computational Social Systems and the Internet, volume 07271 of Dagstuhl Seminar Proceedings, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany, (2007)Bandits with switching costs: T2/3 regret., , , and . STOC, page 459-467. ACM, (2014)Linear Learning with Sparse Data.. CoRR, (2016)Optimal Distributed Online Prediction Using Mini-Batches., , , and . J. Mach. Learn. Res., (2012)Online Learning with Feedback Graphs: Beyond Bandits., , , and . COLT, volume 40 of JMLR Workshop and Conference Proceedings, page 23-35. JMLR.org, (2015)Adaptive Neural Networks for Efficient Inference., , , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 527-536. PMLR, (2017)Better Rates for Any Adversarial Deterministic MDP., and . ICML (3), volume 28 of JMLR Workshop and Conference Proceedings, page 675-683. JMLR.org, (2013)Sparse Multi-Prototype Classification., , and . UAI, page 704-714. AUAI Press, (2018)