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Taylor Expansion of Discount Factors.

, , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 10130-10140. PMLR, (2021)

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An Analysis of Quantile Temporal-Difference Learning., , , , , , , , and . CoRR, (2023)Augment-Reinforce-Merge Policy Gradient for Binary Stochastic Policy., , and . CoRR, (2019)Exploration by Distributional Reinforcement Learning., and . IJCAI, page 2710-2716. ijcai.org, (2018)The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation., , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 29210-29231. PMLR, (2023)VA-learning as a more efficient alternative to Q-learning., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 33739-33757. PMLR, (2023)Understanding Self-Predictive Learning for Reinforcement Learning., , , , , , , , , and 6 other author(s). ICML, volume 202 of Proceedings of Machine Learning Research, page 33632-33656. PMLR, (2023)Biased Gradient Estimate with Drastic Variance Reduction for Meta Reinforcement Learning.. ICML, volume 162 of Proceedings of Machine Learning Research, page 21050-21075. PMLR, (2022)Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces., , , and . CoRR, (2019)Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes., , , and . CoRR, (2019)Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice., , , , , , , , , and 5 other author(s). ICML, volume 202 of Proceedings of Machine Learning Research, page 17135-17175. PMLR, (2023)