Tadashi Kozuno
Orcid: 0000-0002-8820-1362
According to our database1,
Tadashi Kozuno
authored at least 30 papers
between 2017 and 2024.
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Bibliography
2024
Symmetry-aware Reinforcement Learning for Robotic Assembly under Partial Observability with a Soft Wrist.
CoRR, 2024
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees.
CoRR, 2024
2023
Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control With Action Constraints.
IEEE Robotics Autom. Lett., 2023
Multi-Agent Behavior Retrieval: Retrieval-Augmented Policy Training for Cooperative Manipulation by Mobile Robots.
CoRR, 2023
When to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning.
CoRR, 2023
Avoiding Model Estimation in Robust Markov Decision Processes with a Generative Model.
CoRR, 2023
Proceedings of the International Conference on Machine Learning, 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023
2022
Trans. Mach. Learn. Res., 2022
Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences.
J. Mach. Learn. Res., 2022
Confident Approximate Policy Iteration for Efficient Local Planning in q<sup>π</sup>-realizable MDPs.
CoRR, 2022
Proceedings of the 2022 27th OptoElectronics and Communications Conference (OECC) and 2022 International Conference on Photonics in Switching and Computing (PSC), 2022
Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
Model-Free Learning for Two-Player Zero-Sum Partially Observable Markov Games with Perfect Recall.
CoRR, 2021
Identifying Co-Adaptation of Algorithmic and Implementational Innovations in Deep Reinforcement Learning: A Taxonomy and Case Study of Inference-based Algorithms.
CoRR, 2021
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Learning in two-player zero-sum partially observable Markov games with perfect recall.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
2019
Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning.
CoRR, 2019
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2017
CoRR, 2017