Chengchun Shi

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 55

Top Topics

Policy Evaluation

Reinforcement Learning

Markov Decision Process

Infinite Horizon

Top Venues

J. Mach. Learn. Res.

Publications

Danyang Wang, Chengchun Shi, Shikai Luo, Will Wei Sun
Pessimistic Causal Reinforcement Learning with Mediators for Confounded Offline Data. CoRR (2024)
Ting Li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin, Chunbo Lai, Hongtu Zhu
Combining Experimental and Historical Data for Policy Evaluation. CoRR (2024)
Runpeng Dai, Jianing Wang, Fan Zhou, Shikai Luo, Zhiwei Qin, Chengchun Shi, Hongtu Zhu
Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferences. CoRR (2024)
Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi
Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. AISTATS (2024)
Meiling Hao, Pingfan Su, Liyuan Hu, Zoltan Szabo, Qingyuan Zhao, Chengchun Shi
Forward and Backward State Abstractions for Off-policy Evaluation. CoRR (2024)
Qianglin Wen, Chengchun Shi, Ying Yang, Niansheng Tang, Hongtu Zhu
An Analysis of Switchback Designs in Reinforcement Learning. CoRR (2024)
Chengchun Shi, Zhengling Qi, Jianing Wang, Fan Zhou
Value Enhancement of Reinforcement Learning via Efficient and Robust Trust Region Optimization. CoRR (2023)
Yunzhe Zhou, Chengchun Shi, Lexin Li, Qiwei Yao
Testing for the Markov Property in Time Series via Deep Conditional Generative Learning. CoRR (2023)
Tao Ma, Hengrui Cai, Zhengling Qi, Chengchun Shi, Eric B. Laber
Sequential Knockoffs for Variable Selection in Reinforcement Learning. CoRR (2023)
Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi
Robust Offline Policy Evaluation and Optimization with Heavy-Tailed Rewards. CoRR (2023)
Yuhe Gao, Chengchun Shi, Rui Song
Deep Spectral Q-learning with Application to Mobile Health. CoRR (2023)
Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song
A Reinforcement Learning Framework for Dynamic Mediation Analysis. CoRR (2023)
Zeyu Bian, Chengchun Shi, Zhengling Qi, Lan Wang
Off-policy Evaluation in Doubly Inhomogeneous Environments. CoRR (2023)
Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song
A Reinforcement Learning Framework for Dynamic Mediation Analysis. ICML (2023)
Yingying Zhang, Chengchun Shi, Shikai Luo
Conformal Off-Policy Prediction. AISTATS (2023)
Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
Jump Interval-Learning for Individualized Decision Making with Continuous Treatments. J. Mach. Learn. Res. 24 (2023)
Guojun Wu, Ge Song, Xiaoxiang Lv, Shikai Luo, Chengchun Shi, Hongtu Zhu
DNet: Distributional Network for Distributional Individualized Treatment Effects. KDD (2023)
Jitao Wang, Chengchun Shi, Zhenke Wu
A Robust Test for the Stationarity Assumption in Sequential Decision Making. ICML (2023)
Jing-Jing Li, Chengchun Shi, Lexin Li, Anne G. E. Collins
A generalized method for dynamic noise inference in modeling sequential decision-making. CogSci (2023)
Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. AISTATS (2023)
Ting Li, Chengchun Shi, Zhaohua Lu, Yi Li, Hongtu Zhu
Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing. CoRR (2023)
Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. NeurIPS (2023)
Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song
An Instrumental Variable Approach to Confounded Off-Policy Evaluation. ICML (2023)
Ting Li, Chengchun Shi, Jianing Wang, Fan Zhou, Hongtu Zhu
Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making. NeurIPS (2023)
Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song
Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons. CoRR (2022)
Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. CoRR (2022)
Jiayi Wang, Zhengling Qi, Chengchun Shi
Blessing from Experts: Super Reinforcement Learning in Confounded Environments. CoRR (2022)
Chengchun Shi, Runzhe Wan, Ge Song, Shikai Luo, Rui Song, Hongtu Zhu
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets. CoRR (2022)
Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song
An Instrumental Variable Approach to Confounded Off-Policy Evaluation. CoRR (2022)
Yingying Zhang, Chengchun Shi, Shikai Luo
Conformal Off-Policy Prediction. CoRR (2022)
Chengchun Shi, Jin Zhu, Ye Shen, Shikai Luo, Hongtu Zhu, Rui Song
Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process. CoRR (2022)
Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. CoRR (2022)
Liyuan Hu, Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz
Doubly Inhomogeneous Reinforcement Learning. CoRR (2022)
Shikai Luo, Ying Yang, Chengchun Shi, Fang Yao, Jieping Ye, Hongtu Zhu
Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms. CoRR (2022)
Yang Xu, Chengchun Shi, Shikai Luo, Lan Wang, Rui Song
Quantile Off-Policy Evaluation via Deep Conditional Generative Learning. CoRR (2022)
Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz
Reinforcement Learning in Possibly Nonstationary Environments. CoRR (2022)
Masatoshi Uehara, Chengchun Shi, Nathan Kallus
A Review of Off-Policy Evaluation in Reinforcement Learning. CoRR (2022)
Chengchun Shi, Masatoshi Uehara, Jiawei Huang, Nan Jiang
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes. ICML (2022)
Runzhe Wan, Sheng Zhang, Chengchun Shi, Shikai Luo, Rui Song
Pattern Transfer Learning for Reinforcement Learning in Order Dispatching. CoRR (2021)
Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song
An Online Sequential Test for Qualitative Treatment Effects. J. Mach. Learn. Res. 22 (2021)
Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. NeurIPS (2021)
Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
Jump Interval-Learning for Individualized Decision Making. CoRR (2021)
Chengchun Shi, Masatoshi Uehara, Nan Jiang
A Minimax Learning Approach to Off-Policy Evaluation in Partially Observable Markov Decision Processes. CoRR (2021)
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Deeply-Debiased Off-Policy Interval Estimation. CoRR (2021)
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Deeply-Debiased Off-Policy Interval Estimation. ICML (2021)
Chengchun Shi, Tianlin Xu, Wicher Bergsma, Lexin Li
Double Generative Adversarial Networks for Conditional Independence Testing. J. Mach. Learn. Res. 22 (2021)
Chengchun Shi, Yunzhe Zhou, Lexin Li
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning. CoRR (2021)
Chengchun Shi, Wenbin Lu, Rui Song
Breaking the Curse of Nonregularity with Subagging - Inference of the Mean Outcome under Optimal Treatment Regimes. J. Mach. Learn. Res. 21 (2020)
Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. CoRR (2020)
Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space. CoRR (2020)
Chengchun Shi, Xiaoyu Wang, Shikai Luo, Rui Song, Hongtu Zhu, Jieping Ye
A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing. CoRR (2020)
Chengchun Shi, Sheng Zhang, Wenbin Lu, Rui Song
Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings. CoRR (2020)
Chengchun Shi, Tianlin Xu, Wicher Bergsma, Lexin Li
Double Generative Adversarial Networks for Conditional Independence Testing. CoRR (2020)
Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. ICML (2020)
Chengchun Shi, Wenbin Lu, Rui Song
Determining the Number of Latent Factors in Statistical Multi-Relational Learning. J. Mach. Learn. Res. 20 (2019)