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Optimal Dynamic Mechanism Design and the Virtual-Pivot Mechanism.

, , and . Operations Research, 61 (4): 837-854 (2013)

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Regularization Techniques for Learning with Matrices., , and . J. Mach. Learn. Res., (2012)The Nonstochastic Control Problem, , and . (2019)cite arxiv:1911.12178Comment: To appear at Algorithmic Learning Theory (ALT) 2020; small revisions from the last ver.Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?, , , and . (2019)cite arxiv:1910.03016.Online Control with Adversarial Disturbances, , , , and . (2019)cite arxiv:1902.08721.Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes, , , and . (2019)cite arxiv:1908.00261Comment: Additional references and discussion of prior work.Guest editorial: special issue on learning theory., and . Mach. Learn., 80 (2-3): 109-110 (2010)Information Consistency of Nonparametric Gaussian Process Methods., , and . IEEE Trans. Inf. Theory, 54 (5): 2376-2382 (2008)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting., , , and . IEEE Trans. Inf. Theory, 58 (5): 3250-3265 (2012)Stochastic Linear Optimization under Bandit Feedback., , and . COLT, page 355-366. Omnipress, (2008)Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control., , , , and . ICLR (Poster), OpenReview.net, (2019)