Masatoshi Uehara
Orcid: 0000-0001-9017-3105
According to our database1,
Masatoshi Uehara
authored at least 49 papers
between 2018 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
CoRR, 2024
CoRR, 2024
2023
CoRR, 2023
Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the International Conference on Machine Learning, 2023
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Minimax Instrumental Variable Regression and L<sub>2</sub> Convergence Guarantees without Identification or Closedness.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning.
Oper. Res., November, 2022
Optimal Fixed-Budget Best Arm Identification using the Augmented Inverse Probability Weighting Estimator in Two-Armed Gaussian Bandits with Unknown Variances.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach.
Proceedings of the International Conference on Machine Learning, 2022
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
A Minimax Learning Approach to Off-Policy Evaluation in Partially Observable Markov Decision Processes.
CoRR, 2021
Pessimistic Model-based Offline RL: PAC Bounds and Posterior Sampling under Partial Coverage.
CoRR, 2021
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage.
CoRR, 2021
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach.
CoRR, 2021
Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency.
CoRR, 2021
Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage.
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
Proceedings of the Conference on Learning Theory, 2021
2020
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes.
J. Mach. Learn. Res., 2020
Efficient Evaluation of Natural Stochastic Policies in Offline Reinforcement Learning.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond.
CoRR, 2019
Efficiently Breaking the Curse of Horizon: Double Reinforcement Learning in Infinite-Horizon Processes.
CoRR, 2019
CoRR, 2019
Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
2018
Analysis of Noise Contrastive Estimation from the Perspective of Asymptotic Variance.
CoRR, 2018