Masatoshi Uehara
- Statistics and Probability top 10%
- Advanced Causal Inference Techniques 4
- Statistical Methods and Inference 4
- Statistical Methods and Bayesian Inference 2
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- Advanced Bandit Algorithms Research 3
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- Supply Chain and Inventory Management 1
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- Reinforcement Learning in Robotics 7
- Machine Learning in Healthcare 1
- Machine Learning and Algorithms 1
- Co-authors
- Nathan KallusJonathan ChangXiaojie MaoYusuke NaritaRahul KidambiJae Kwang KimNobuyuki ShimizuTakashi Takenouchi
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchManagement Information Systems
- Journals
- Biometrika (1 paper)Operations Research (1 paper)Mathematics of Operations Research (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Masatoshi Uehara
12 papers receiving 51 citations
Peers
Comparison fields: 5 of 29
- Statistics and Probability 26
- Management Science and Operations Research 16
- Management Information Systems 6
- Artificial Intelligence 18
- Computer Networks and Communications 9
Countries citing papers authored by Masatoshi Uehara
This map shows the geographic impact of Masatoshi Uehara's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Masatoshi Uehara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masatoshi Uehara more than expected).
Fields of papers citing papers by Masatoshi Uehara
This network shows the impact of papers produced by Masatoshi Uehara. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Masatoshi Uehara. The network helps show where Masatoshi Uehara may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Masatoshi Uehara, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2023 | 3 | |
| 3 | 2023 | 5 | |
| 4 | 2023 | 0 | |
| 5 | 2022 | 19 | |
| 6 | Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage | 2021 | 3 |
| 7 | Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies | 2020 | 1 |
| 8 | A Unified Statistically Efficient Estimation Framework for Unnormalized Models | 2020 | 2 |
| 9 | Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes | 2020 | 5 |
| 10 | Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation | 2020 | 1 |
| 11 | Efficiently Breaking the Curse of Horizon: Double Reinforcement Learning in Infinite-Horizon Processes. | 2019 | 7 |
| 12 | Localized Debiased Machine Learning: Efficient Estimation of Quantile Treatment Effects, Conditional Value at Risk, and Beyond. | 2019 | 3 |
| 13 | Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning | 2019 | 3 |
| 14 | Imputation estimators for unnormalized models with missing data. | 2019 | 1 |
About Masatoshi Uehara
Masatoshi Uehara is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research, having authored 14 papers that have together received 53 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Advanced Causal Inference Techniques (4 papers), Statistical Methods and Inference (4 papers), Advanced Bandit Algorithms Research (3 papers), Statistical Methods and Bayesian Inference (2 papers), Supply Chain and Inventory Management (1 paper), Machine Learning in Healthcare (1 paper) and Machine Learning and Algorithms (1 paper). The work is most often cited by research in Statistics and Probability (26 citations), Management Science and Operations Research (16 citations) and Management Information Systems (6 citations). Masatoshi Uehara has collaborated with scholars based in United States and Japan. Frequent co-authors include Nathan Kallus, Jonathan Chang, Xiaojie Mao, Yusuke Narita, Rahul Kidambi, Jae Kwang Kim, Nobuyuki Shimizu, Takashi Takenouchi, Takafumi Kanamori and Yuta Saito. Their work appears in journals such as Biometrika, Operations Research and Mathematics of Operations Research.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.