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    • International Conferences
      Reinforcement Learning World Model

      Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice

      Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Remi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvari, Wataru Kumagai, Yutaka Matsuo

      International Conference on Machine Learning (ICML 2023). July 2023.

    • International Conferences
      Reinforcement Learning World Model

      Generalized Decision Transformer for Offline Hindsight Infomation Matching

      Hiroki Furuta, Yutaka Matsuo, and Shixiang Shane Gu

      International Conference on Learning Representations 2022 (ICLR2022, Spotlight).

    • International Conferences
      Reinforcement Learning Representation Learning Theory

      Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning

      Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, and Shixiang Shane Gu.

      Advances in Neural Information Processing Systems 2021 (NeurIPS2021). December 2021.

    • International Conferences
      Reinforcement Learning Representation Learning Theory

      Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning

      Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, and Shixiang Shane Gu

      International Conference on Machine Learning 2021 (ICML2021).

    • International Conferences
      Reinforcement Learning Representation Learning Theory

      Identifying Co-Adaptation of Algorithmic and implementational Innovations in Deep Reinforcement Learning: Taxonomy of Inference-based Algorithms

      Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Shane Gu.

      International Conference on Machine Learning 2021 (ICML2021).

    • International Conferences
      Reinforcement Learning Representation Learning Theory

      Reward and Optimality Empowerments: Information-Theoretic Measures for Task Complexity in Deep Reinforcement Learning

      Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, and Shixiang Shane Gu.

      International Conference on Machine Learning 2021 (ICML2021). July 2021. [paper]

    • International Conferences
      Reinforcement Learning Robotics

      Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

      Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, and Shixiang Shane Gu.

      International Conference on Learning Representations 2021 (ICLR2021).