| High-dimensional A-learning for optimal dynamic treatment regimes C Shi, A Fan, R Song, W Lu Annals of statistics 46 (3), 925, 2018 | 147 | 2018 |
| A review of off-policy evaluation in reinforcement learning M Uehara, C Shi, N Kallus arXiv preprint arXiv:2212.06355, 2022 | 142 | 2022 |
| Statistical inference of the value function for reinforcement learning in infinite-horizon settings C Shi, S Zhang, W Lu, R Song Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 139 | 2022 |
| A massive data framework for M-estimators with cubic-rate C Shi, W Lu, R Song Journal of the American Statistical Association 113 (524), 1698-1709, 2018 | 93 | 2018 |
| Dynamic causal effects evaluation in a/b testing with a reinforcement learning framework C Shi, X Wang, S Luo, H Zhu, J Ye, R Song Journal of the American Statistical Association 118 (543), 2059-2071, 2023 | 82 | 2023 |
| Linear hypothesis testing for high dimensional generalized linear models C Shi, R Song, Z Chen, R Li Annals of statistics 47 (5), 2671, 2019 | 79 | 2019 |
| Statistical inference for high-dimensional models via recursive online-score estimation C Shi, R Song, W Lu, R Li Journal of the American Statistical Association 116 (535), 1307-1318, 2021 | 71 | 2021 |
| Off-policy confidence interval estimation with confounded markov decision process C Shi, J Zhu, Y Shen, S Luo, H Zhu, R Song Journal of the American Statistical Association 119 (545), 273-284, 2024 | 68 | 2024 |
| Fin-r1: A large language model for financial reasoning through reinforcement learning LZ Zhaowei Liu, Xin Guo, Zhi Yang, Fangqi Lou, Lingfeng Zeng, Mengping Li ... arXiv preprint arXiv:2503.16252, 2025 | 64 | 2025 |
| A minimax learning approach to off-policy evaluation in confounded partially observable markov decision processes C Shi, M Uehara, J Huang, N Jiang International Conference on Machine Learning, 20057-20094, 2022 | 62 | 2022 |
| Does the markov decision process fit the data: Testing for the markov property in sequential decision making C Shi, R Wan, R Song, W Lu, L Leng International Conference on Machine Learning, 8807-8817, 2020 | 60 | 2020 |
| simplexreg: An R package for regression analysis of proportional data using the simplex distribution P Zhang, Z Qiu, C Shi Journal of Statistical Software 71, 1-21, 2016 | 54 | 2016 |
| Deeply-debiased off-policy interval estimation C Shi, R Wan, V Chernozhukov, R Song International conference on machine learning, 9580-9591, 2021 | 52 | 2021 |
| Double generative adversarial networks for conditional independence testing C Shi, T Xu, W Bergsma, L Li Journal of Machine Learning Research 22 (285), 1-32, 2021 | 42 | 2021 |
| Maximin projection learning for optimal treatment decision with heterogeneous individualized treatment effects C Shi, R Song, W Lu, B Fu Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2018 | 42 | 2018 |
| Robust learning for optimal treatment decision with np-dimensionality C Shi, R Song, W Lu Electronic journal of statistics 10, 2894, 2016 | 41 | 2016 |
| Breaking the Curse of Nonregularity with Subagging---Inference of the Mean Outcome under Optimal Treatment Regimes C Shi, W Lu, R Song Journal of Machine Learning Research 21 (176), 1-67, 2020 | 40 | 2020 |
| Future-dependent value-based off-policy evaluation in pomdps M Uehara, H Kiyohara, A Bennett, V Chernozhukov, N Jiang, N Kallus, ... Advances in neural information processing systems 36, 15991-16008, 2023 | 35 | 2023 |
| An instrumental variable approach to confounded off-policy evaluation Y Xu, J Zhu, C Shi, S Luo, R Song International Conference on Machine Learning, 38848-38880, 2023 | 32 | 2023 |
| Testing mediation effects using logic of boolean matrices C Shi, L Li Journal of the American Statistical Association 117 (540), 2014-2027, 2022 | 29 | 2022 |
Rui SongNorth Carolina State UniversityVerified email at ncsu.edu
