Kumagai, Wataru

10 publications

ICLR 2025 Near-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

NeurIPS 2025 Provably Efficient RL Under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation Toshinori Kitamura, Arnob Ghosh, Tadashi Kozuno, Wataru Kumagai, Kazumi Kasaura, Kenta Hoshino, Yohei Hosoe, Yutaka Matsuo

MLOSS 2024 Invariant and Equivariant Reynolds Networks Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai

NeurIPSW 2023 Local Acquisition Function for Active Level Set Estimation Yuta Kokubun, Kota Matsui, Kentaro Kutsukake, Wataru Kumagai, Takafumi Kanamori

ICML 2023 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 Menard, Mohammad Gheshlaghi Azar, Remi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvari, Wataru Kumagai, Yutaka Matsuo

NeurIPS 2022 Langevin Autoencoders for Learning Deep Latent Variable Models Shohei Taniguchi, Yusuke Iwasawa, Wataru Kumagai, Yutaka Matsuo

ICLR 2021 Group Equivariant Conditional Neural Processes Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo

MLJ 2019 Risk Bound of Transfer Learning Using Parametric Feature Mapping and Its Application to Sparse Coding Wataru Kumagai, Takafumi Kanamori

NeurIPS 2017 Regret Analysis for Continuous Dueling Bandit Wataru Kumagai

NeurIPS 2016 Learning Bound for Parameter Transfer Learning Wataru Kumagai