default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDTadashi Kozuno
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c16]Kohei Honda, Ryo Yonetani, Mai Nishimura, Tadashi Kozuno:
When to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning. ICRA 2024: 6650-6656- [c15]Hai Nguyen, Tadashi Kozuno, Cristian C. Beltran-Hernandez, Masashi Hamaya:
Symmetry-aware Reinforcement Learning for Robotic Assembly under Partial Observability with a Soft Wrist. ICRA 2024: 9369-9375 - [i24]Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato, Yuki Ichihara, Soichiro Nishimori, Akiyoshi Sannai, Sho Sonoda, Wataru Kumagai, Yutaka Matsuo:
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees. CoRR abs/2401.17780 (2024) - [i23]Hai Nguyen, Tadashi Kozuno, Cristian C. Beltran-Hernandez, Masashi Hamaya:
Symmetry-aware Reinforcement Learning for Robotic Assembly under Partial Observability with a Soft Wrist. CoRR abs/2402.18002 (2024) - [i22]Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai, Kenta Hoshino, Yohei Hosoe, Kazumi Kasaura, Masashi Hamaya, Paavo Parmas, Yutaka Matsuo:
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form. CoRR abs/2408.16286 (2024) - 2023
- [j3]Kazumi Kasaura
, Shuwa Miura, Tadashi Kozuno, Ryo Yonetani, Kenta Hoshino, Yohei Hosoe:
Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control With Action Constraints. IEEE Robotics Autom. Lett. 8(8): 4449-4456 (2023) - [c14]Hikaru Asano, Ryo Yonetani, Mai Nishimura, Tadashi Kozuno:
Counterfactual Fairness Filter for Fair-Delay Multi-Robot Navigation. AAMAS 2023: 887-895 - [c13]Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko:
Adapting to game trees in zero-sum imperfect information games. ICML 2023: 10093-10135 - [c12]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:
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice. ICML 2023: 17135-17175 - [c11]Yunhao Tang, Tadashi Kozuno, Mark Rowland, Anna Harutyunyan, Rémi Munos, Bernardo Ávila Pires, Michal Valko:
DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm. ICML 2023: 33657-33673 - [i21]Wenhao Yang, Han Wang, Tadashi Kozuno, Scott M. Jordan, Zhihua Zhang:
Avoiding Model Estimation in Robust Markov Decision Processes with a Generative Model. CoRR abs/2302.01248 (2023) - [i20]Kazumi Kasaura, Shuwa Miura, Tadashi Kozuno, Ryo Yonetani, Kenta Hoshino, Yohei Hosoe:
Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control with Action Constraints. CoRR abs/2304.08743 (2023) - [i19]Kohei Honda, Ryo Yonetani, Mai Nishimura, Tadashi Kozuno:
When to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning. CoRR abs/2304.12046 (2023) - [i18]Hikaru Asano, Ryo Yonetani, Mai Nishimura, Tadashi Kozuno:
Counterfactual Fairness Filter for Fair-Delay Multi-Robot Navigation. CoRR abs/2305.11465 (2023) - [i17]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:
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice. CoRR abs/2305.13185 (2023) - [i16]Yunhao Tang, Tadashi Kozuno, Mark Rowland, Anna Harutyunyan, Rémi Munos, Bernardo Ávila Pires, Michal Valko:
DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm. CoRR abs/2305.18501 (2023) - [i15]Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko:
Local and adaptive mirror descents in extensive-form games. CoRR abs/2309.00656 (2023) - [i14]So Kuroki, Mai Nishimura, Tadashi Kozuno:
Multi-Agent Behavior Retrieval: Retrieval-Augmented Policy Training for Cooperative Manipulation by Mobile Robots. CoRR abs/2312.02008 (2023) - 2022
- [j2]Alan Chan, Hugo Silva, Sungsu Lim, Tadashi Kozuno, A. Rupam Mahmood, Martha White:
Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences. J. Mach. Learn. Res. 23: 253:1-253:79 (2022) - [j1]Han Wang, Archit Sakhadeo, Adam M. White, James Bell, Vincent Liu, Xutong Zhao, Puer Liu, Tadashi Kozuno, Alona Fyshe, Martha White:
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL. Trans. Mach. Learn. Res. 2022 (2022) - [c10]Dongqi Han, Tadashi Kozuno, Xufang Luo, Zhao-Yun Chen, Kenji Doya, Yuqing Yang, Dongsheng Li:
Variational oracle guiding for reinforcement learning. ICLR 2022 - [c9]Gellért Weisz, András György, Tadashi Kozuno, Csaba Szepesvári:
Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs. NeurIPS 2022 - [c8]Shinnosuke Yagi, Mutsuki Nakahara, Kosuke Suzuoki, Tadashi Kozuno, Daisuke Hisano:
Deep Learning-based Nonlinear Quantizer for Fronthaul Compression. OECC/PSC 2022: 1-3 - [i13]Han Wang, Archit Sakhadeo, Adam White, James Bell, Vincent Liu, Xutong Zhao, Puer Liu, Tadashi Kozuno, Alona Fyshe, Martha White:
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL. CoRR abs/2205.08716 (2022) - [i12]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:
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal. CoRR abs/2205.14211 (2022) - [i11]Gellért Weisz, András György, Tadashi Kozuno, Csaba Szepesvári:
Confident Approximate Policy Iteration for Efficient Local Planning in qπ-realizable MDPs. CoRR abs/2210.15755 (2022) - [i10]Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko:
Adapting to game trees in zero-sum imperfect information games. CoRR abs/2212.12567 (2022) - 2021
- [c7]Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu:
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning. ICML 2021: 3541-3552 - [c6]Tadashi Kozuno, Yunhao Tang, Mark Rowland, Rémi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel:
Revisiting Peng's Q(λ) for Modern Reinforcement Learning. ICML 2021: 5794-5804 - [c5]Yunhao Tang, Tadashi Kozuno, Mark Rowland, Rémi Munos, Michal Valko:
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation. NeurIPS 2021: 5303-5315 - [c4]Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Shane Gu:
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning. NeurIPS 2021: 9828-9842 - [c3]Tadashi Kozuno, Pierre Ménard, Rémi Munos, Michal Valko:
Learning in two-player zero-sum partially observable Markov games with perfect recall. NeurIPS 2021: 11987-11998 - [i9]Tadashi Kozuno, Yunhao Tang, Mark Rowland, Rémi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel:
Revisiting Peng's Q(λ) for Modern Reinforcement Learning. CoRR abs/2103.00107 (2021) - [i8]Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Shane Gu:
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning. CoRR abs/2103.12726 (2021) - [i7]Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima, Yutaka Matsuo, Shixiang Shane Gu:
Identifying Co-Adaptation of Algorithmic and Implementational Innovations in Deep Reinforcement Learning: A Taxonomy and Case Study of Inference-based Algorithms. CoRR abs/2103.17258 (2021) - [i6]Tadashi Kozuno, Pierre Ménard, Rémi Munos, Michal Valko:
Model-Free Learning for Two-Player Zero-Sum Partially Observable Markov Games with Perfect Recall. CoRR abs/2106.06279 (2021) - [i5]Yunhao Tang, Tadashi Kozuno, Mark Rowland, Rémi Munos, Michal Valko:
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation. CoRR abs/2106.13125 (2021) - [i4]Alan Chan, Hugo Silva, Sungsu Lim, Tadashi Kozuno, A. Rupam Mahmood, Martha White:
Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences. CoRR abs/2107.08285 (2021) - 2020
- [c2]Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist:
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning. NeurIPS 2020 - [i3]Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist:
Leverage the Average: an Analysis of Regularization in RL. CoRR abs/2003.14089 (2020)
2010 – 2019
- 2019
- [c1]Tadashi Kozuno, Eiji Uchibe, Kenji Doya:
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning. AISTATS 2019: 2995-3003 - [i2]Tadashi Kozuno, Dongqi Han, Kenji Doya:
Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning. CoRR abs/1906.07586 (2019) - 2017
- [i1]Tadashi Kozuno, Eiji Uchibe, Kenji Doya:
Unifying Value Iteration, Advantage Learning, and Dynamic Policy Programming. CoRR abs/1710.10866 (2017)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-04 20:59 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
