Toshinori Kitamura

16 papers A* 3C 2Journal 11
YearRankTypeTitle / Venue / Authors
2025 A* conf
A Comprehensive Survey on Physical Risk Control in the Era of Foundation Model-enabled Robotics.
IJCAI
Takeshi Kojima, Yaonan Zhu, Yusuke Iwasawa, Toshinori Kitamura, Gang Yan, Shu Morikuni, Ryosuke Takanami, Alfredo Solano, Tatsuya Matsushima, Akiko Murakami, Yutaka Matsuo
2025 J jnl
A Comprehensive Survey on Physical Risk Control in the Era of Foundation Model-enabled Robotics.
CoRR
Takeshi Kojima, Yaonan Zhu, Yusuke Iwasawa, Toshinori Kitamura, Gang Yan, Shu Morikuni, Ryosuke Takanami, Alfredo Solano, Tatsuya Matsushima, Akiko Murakami, Yutaka Matsuo
2025 A* conf
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form.
ICLR
Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai, Kenta Hoshino, Yohei Hosoe, Kazumi Kasaura, Masashi Hamaya, Paavo Parmas, Yutaka Matsuo
2025 J jnl
Provably Efficient RL under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation.
CoRR
Toshinori Kitamura, Arnob Ghosh, Tadashi Kozuno, Wataru Kumagai, Kazumi Kasaura, Kenta Hoshino, Yohei Hosoe, Yutaka Matsuo
2024 J jnl
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees.
CoRR
Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato, Yuki Ichihara, Soichiro Nishimori, Akiyoshi Sannai, Sho Sonoda, Wataru Kumagai, Yutaka Matsuo
2024 J jnl
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form.
CoRR
Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai, Kenta Hoshino, Yohei Hosoe, Kazumi Kasaura, Masashi Hamaya, Paavo Parmas, Yutaka Matsuo
2023 A* conf
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice.
ICML
Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo
2023 J jnl
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice.
CoRR
Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo
2022 J jnl
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal.
CoRR
Tadashi Kozuno, Wenhao Yang, Nino Vieillard, Toshinori Kitamura, Yunhao Tang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Michal Valko, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári
2021 C conf
Cautious Actor-Critic.
ACML
Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara
2021 J jnl
Cautious Actor-Critic.
CoRR
Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara
2021 J jnl
Cautious Policy Programming: Exploiting KL Regularization in Monotonic Policy Improvement for Reinforcement Learning.
CoRR
Lingwei Zhu, Toshinori Kitamura, Takamitsu Matsubara
2021 C conf
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning.
ACML
Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara
2021 J jnl
Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning.
CoRR
Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara
2021 J jnl
ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives.
CoRR
Toshinori Kitamura, Ryo Yonetani
2011 J jnl
Internet and mobile phone text-messaging dependency: Factor structure and correlation with dysphoric mood among Japanese adults.
Comput. Hum. Behav.
Xi Lu, Junko Watanabe, Qingbo Liu, Masayo Uji, Masahiro Shono, Toshinori Kitamura