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Li, Ting, Shi, Chengchun ORCID: 0000-0001-7773-2099, Lu, Zhaohua, Li, Yi and Zhu, Hongtu
(2024)
Evaluating dynamic conditional quantile treatment effects with applications in ridesharing.
Journal of the American Statistical Association, 119 (547).
1736 - 1750.
ISSN 0162-1459
Li, Ting, Shi, Chengchun ORCID: 0000-0001-7773-2099, Wen, Qianglin, Sui, Yang, Qin, Yongli, Lai, Chunbo and Zhu, Hongtu
(2024)
Combining experimental and historical data for policy evaluation.
Proceedings of Machine Learning Research, 235.
pp. 28630-28656.
ISSN 2640-3498
Luo, Shikai, Yang, Ying, Shi, Chengchun ORCID: 0000-0001-7773-2099, Yao, Fang, Ye, Jieping and Zhu, Hongtu
(2024)
Policy evaluation for temporal and/or spatial dependent experiments.
Journal of the Royal Statistical Society. Series B: Statistical Methodology, 86 (3).
623 - 649.
ISSN 1369-7412
Li, Ting, Shi, Chengchun ORCID: 0000-0001-7773-2099, Wang, Jianing, Zhou, Fan and Zhu, Hongtu
(2023)
Optimal treatment allocation for efficient policy evaluation in sequential decision making.
In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. and Levine, S., (eds.)
Advances in Neural Information Processing Systems 36 (NeurIPS 2023).
Neural Information Processing Systems Foundation.
Shi, Chengchun ORCID: 0000-0001-7773-2099, Wan, Runzhe, Song, Ge, Luo, Shikai, Zhu, Hongtu and Song, Rui
(2023)
A multiagent reinforcement learning framework for off-policy evaluation in two-sided markets.
Annals of Applied Statistics, 17 (4).
2701 - 2722.
ISSN 1932-6157
Wu, Guojun, Song, Ge, Lv, Xiaoxiang, Luo, Shikai, Shi, Chengchun ORCID: 0000-0001-7773-2099 and Zhu, Hongtu
(2023)
DNet: distributional network for distributional individualized treatment effects.
Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
5215 - 5224.
ISSN 2154-817X
Shi, Chengchun ORCID: 0000-0001-7773-2099, Zhu, Jin, Shen, Ye, Luo, Shikai, Zhu, Hongtu and Song, Rui
(2022)
Off-policy confidence interval estimation with confounded Markov decision process.
Journal of the American Statistical Association.
ISSN 0162-1459
Shi, Chengchun ORCID: 0000-0001-7773-2099, Luo, Shikai, Le, Yuan, Zhu, Hongtu and Song, Rui
(2022)
Statistically efficient advantage learning for offline reinforcement learning in infinite horizons.
Journal of the American Statistical Association.
ISSN 0162-1459
Shi, Chengchun ORCID: 0000-0001-7773-2099, Wang, Xiaoyu, Luo, Shikai, Zhu, Hongtu, Ye, Jieping and Song, Rui
(2022)
Dynamic causal effects evaluation in A/B testing with a reinforcement learning framework.
Journal of the American Statistical Association.
1 - 13.
ISSN 0162-1459
Shi, Chengchun ORCID: 0000-0001-7773-2099, Luo, Shikai, Zhu, Hongtu and Song, Rui
(2021)
An online sequential test for qualitative treatment effects.
Journal of Machine Learning Research, 22.
ISSN 1532-4435