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Recurrent Experience Replay in Distributed Reinforcement Learning., , , , and . ICLR (Poster), OpenReview.net, (2019)The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning., , , , , and . ICLR (Poster), OpenReview.net, (2018)Noisy Networks For Exploration., , , , , , , , , and 3 other author(s). ICLR (Poster), OpenReview.net, (2018)Optimistic planning for belief-augmented Markov Decision Processes., , and . ADPRL, page 77-84. IEEE, (2013)Finite-sample analysis of least-squares policy iteration., , and . J. Mach. Learn. Res., (2012)Analysis of a Classification-based Policy Iteration Algorithm., , and . ICML, page 607-614. Omnipress, (2010)On the Sample Complexity of Reinforcement Learning with a Generative Model ., , and . ICML, icml.cc / Omnipress, (2012)Minimax Number of Strata for Online Stratified Sampling Given Noisy Samples., and . ALT, volume 7568 of Lecture Notes in Computer Science, page 229-244. Springer, (2012)α-Rank: Multi-Agent Evaluation by Evolution., , , , , , , , , and . CoRR, (2019)Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem., , , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 10-18. JMLR.org, (2014)