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Tadashi Kozuno

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

15

Venues

7

Active years

2019–2025

Best venue rank

A*

Where they publish

Papers

15 indexed papers, newest first.

YearVenueTitleAuthors
2025ICLRNear-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form.Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai, Kenta Hoshino, Yohei Hosoe, Kazumi Kasaura, Masashi Hamaya, Paavo Parmas, Yutaka Matsuo
2025ICMLThe Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback.Cme Fiegel, Pierre Mnard, Tadashi Kozuno, Michal Valko, Vianney Perchet
2024ECCVHand2Any: Hand-to-Any Motion Mapping with Few-Shot User Adaptation for Avatar Manipulation.Riku Shinohara, Atsushi Hashimoto, Tadashi Kozuno, Shigeo Yoshida, Yutaro Hirao, Monica Perusqua-Hernndez, Hideaki Uchiyama, Kiyoshi Kiyokawa
2024ICRAWhen to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning.Kohei Honda, Ryo Yonetani, Mai Nishimura, Tadashi Kozuno
2024ICRASymmetry-aware Reinforcement Learning for Robotic Assembly under Partial Observability with a Soft Wrist.Hai Nguyen, Tadashi Kozuno, Cristian C. Beltran-Hernandez, Masashi Hamaya
2024IROSMulti-Agent Behavior Retrieval: Retrieval-Augmented Policy Training for Cooperative Push Manipulation by Mobile Robots.So Kuroki, Mai Nishimura, Tadashi Kozuno
2024IROSLanguage-Guided Pattern Formation for Swarm Robotics with Multi-Agent Reinforcement Learning.Hsu-Shen Liu, So Kuroki, Tadashi Kozuno, Wei-Fang Sun, Chun-Yi Lee
2024ISMARHand2Any: Real-time Avatar Manipulation through Hand-to-Any Motion Mapping with Few-Shot User Adaptation.Riku Shinohara, Atsushi Hashimoto, Tadashi Kozuno, Shigeo Yoshida, Yutaro Hirao, Monica Perusqua-Hernndez, Hideaki Uchiyama, Kiyoshi Kiyokawa
2023ICMLAdapting to game trees in zero-sum imperfect information games.Cme Fiegel, Pierre Mnard, Tadashi Kozuno, Rmi Munos, Vianney Perchet, Michal Valko
2023ICMLRegularization 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 Mnard, Mohammad Gheshlaghi Azar, Rmi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvri, Wataru Kumagai, Yutaka Matsuo
2023ICMLDoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm.Yunhao Tang, Tadashi Kozuno, Mark Rowland, Anna Harutyunyan, Rmi Munos, Bernardo vila Pires, Michal Valko
2022ICLRVariational oracle guiding for reinforcement learning.Dongqi Han, Tadashi Kozuno, Xufang Luo, Zhao-Yun Chen, Kenji Doya, Yuqing Yang, Dongsheng Li
2021ICMLPolicy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning.Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu
2021ICMLRevisiting Peng's Q(λ) for Modern Reinforcement Learning.Tadashi Kozuno, Yunhao Tang, Mark Rowland, Rmi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel
2019AISTATSTheoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning.Tadashi Kozuno, Eiji Uchibe, Kenji Doya