Items where Author is "Zhu, Hongtu"

Article

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

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

Book Section

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.