Wataru Kumagai

46 papers A* 4B 5C 1Journal 32Unranked 4

Year	Rank	Type	Title / Venue / Authors
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 Dataset for Evaluating LLM-based Evaluation Functions for Research Question Extraction Task. CoRR Yuya Fujisaki, Shiro Takagi, Hideki Asoh, Wataru Kumagai
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`	Invariant and Equivariant Reynolds Networks. J. Mach. Learn. Res. Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai
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
2024	J	`jnl`	Universal approximation with neural networks on function spaces. J. Exp. Theor. Artif. Intell. Wataru Kumagai, Akiyoshi Sannai, Makoto Kawano
2023	—	`conf`	A Switching Normalization Method in Decomposition-based Constraint Handling for Constrained Optimization. SICE Yusuke Yasuda, Hidetoki Kojima, Wataru Kumagai, Kenichi Tamura, Keiichiro Yasuda
2023	J	`jnl`	LPML: LLM-Prompting Markup Language for Mathematical Reasoning. CoRR Ryutaro Yamauchi, Sho Sonoda, Akiyoshi Sannai, Wataru Kumagai
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
2023	J	`jnl`	Towards Autonomous Hypothesis Verification via Language Models with Minimal Guidance. CoRR Shiro Takagi, Ryutaro Yamauchi, Wataru Kumagai
2022	A*	`conf`	Langevin Autoencoders for Learning Deep Latent Variable Models. NeurIPS Shohei Taniguchi, Yusuke Iwasawa, Wataru Kumagai, Yutaka Matsuo
2022	J	`jnl`	Langevin Autoencoders for Learning Deep Latent Variable Models. CoRR Shohei Taniguchi, Yusuke Iwasawa, Wataru Kumagai, Yutaka Matsuo
2022	—	`conf`	MOEA/D with Feasibility-based Weight Adjustment for Constrained Optimization. SSCI Yusuke Yasuda, Wataru Kumagai, Kenichi Tamura, Keiichiro Yasuda
2021	J	`jnl`	Equivariant and Invariant Reynolds Networks. CoRR Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai
2021	A*	`conf`	Group Equivariant Conditional Neural Processes. ICLR Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
2021	J	`jnl`	Group Equivariant Conditional Neural Processes. CoRR Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
2021	J	`jnl`	Uncertainty propagation for dropout-based Bayesian neural networks. Neural Networks Yuki Mae, Wataru Kumagai, Takafumi Kanamori
2020	J	`jnl`	Universal Approximation Theorem for Equivariant Maps by Group CNNs. CoRR Wataru Kumagai, Akiyoshi Sannai
2019	J	`jnl`	Risk bound of transfer learning using parametric feature mapping and its application to sparse coding. Mach. Learn. Wataru Kumagai, Takafumi Kanamori
2019	J	`jnl`	Robust Label Prediction via Label Propagation and Geodesic IEICE Trans. Inf. Syst. Yuichiro Wada, Siqiang Su, Wataru Kumagai, Takafumi Kanamori
2019	J	`jnl`	Spectral Embedded Deep Clustering. Entropy Yuichiro Wada, Shugo Miyamoto, Takumi Nakagama, Léo Andéol, Wataru Kumagai, Takafumi Kanamori
2019	J	`jnl`	Variable Selection for Nonparametric Learning with Power Series Kernels. Neural Comput. Kota Matsui, Wataru Kumagai, Kenta Kanamori, Mitsuaki Nishikimi, Takafumi Kanamori
2018	J	`jnl`	Corrections to "Random Number Conversion and LOCC Conversion via Restricted Storage". IEEE Trans. Inf. Theory Wataru Kumagai, Masahito Hayashi
2018	J	`jnl`	Corrections to "Second-Order Asymptotics of Conversions of Distributions and Entangled States Based on Rayleigh-Normal Probability Distributions". IEEE Trans. Inf. Theory Wataru Kumagai, Masahito Hayashi
2018	C	`conf`	Introduction to Bandit Convex Optimization Algorithms. ISITA Wataru Kumagai
2018	B	`conf`	Particle Swarm Optimization with Rotational Invariance Using Correlativity. SMC Wataru Kumagai, Keiichiro Yasuda
2018	J	`jnl`	Variable Selection for Nonparametric Learning with Power Series Kernels. CoRR Kota Matsui, Wataru Kumagai, Kenta Kanamori, Mitsuaki Nishikimi, Takafumi Kanamori
2017	J	`jnl`	Parallel distributed block coordinate descent methods based on pairwise comparison oracle. J. Glob. Optim. Kota Matsui, Wataru Kumagai, Takafumi Kanamori
2017	J	`jnl`	Random Number Conversion and LOCC Conversion via Restricted Storage. IEEE Trans. Inf. Theory Wataru Kumagai, Masahito Hayashi
2017	—	`conf`	Regret Analysis for Continuous Dueling Bandit. NIPS Wataru Kumagai
2017	J	`jnl`	Regret Analysis for Continuous Dueling Bandit. CoRR Wataru Kumagai
2017	J	`jnl`	Second-Order Asymptotics of Conversions of Distributions and Entangled States Based on Rayleigh-Normal Probability Distributions. IEEE Trans. Inf. Theory Wataru Kumagai, Masahito Hayashi
2016	—	`conf`	Learning Bound for Parameter Transfer Learning. NIPS Wataru Kumagai
2016	J	`jnl`	Learning Bound for Parameter Transfer Learning. CoRR Wataru Kumagai
2015	J	`jnl`	Asymptotic Compatibility between LOCC Conversion and Recovery. CoRR Kosuke Ito, Wataru Kumagai, Masahito Hayashi
2015	B	`conf`	Search Dynamics Analysis and Adaptive Parameter Adjustment of Cuckoo Search. SMC Wataru Kumagai, Kenichi Tamura, Keiichiro Yasuda
2014	B	`conf`	Asymptotic reversibility of LOCC conversions. ISIT Kosuke Ito, Wataru Kumagai, Masahito Hayashi
2014	J	`jnl`	Parallel Distributed Block Coordinate Descent Methods based on Pairwise Comparison Oracle. CoRR Kota Matsui, Wataru Kumagai, Takafumi Kanamori
2014	J	`jnl`	Random Number Conversion and LOCC Conversion via Restricted Storage. CoRR Wataru Kumagai, Masahito Hayashi
2014	B	`conf`	Random number conversion via restricted storage. ISIT Wataru Kumagai, Masahito Hayashi
2013	J	`jnl`	Second Order Asymptotics for Random Number Generation CoRR Wataru Kumagai, Masahito Hayashi
2013	J	`jnl`	Second Order Asymptotics of Optimal Approximate Conversion for Probability Distributions and Entangled States and Its Application to LOCC Cloning. CoRR Wataru Kumagai, Masahito Hayashi
2013	B	`conf`	Second order asymptotics for random number generation. ISIT Wataru Kumagai, Masahito Hayashi
2007	J	`jnl`	Toward Separating Integer Factoring from Discrete Logarithm mod IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Shuji Isobe, Wataru Kumagai, Masahiro Mambo, Hiroki Shizuya