Chengchun Shi

According to our database, Chengchun Shi authored at least 42 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

An Analysis of Switchback Designs in Reinforcement Learning.

Qianglin Wen, Chengchun Shi, Ying Yang, Niansheng Tang, Hongtu Zhu

CoRR, 2024

Pessimistic Causal Reinforcement Learning with Mediators for Confounded Offline Data.

Danyang Wang, Chengchun Shi, Shikai Luo, Will Wei Sun

CoRR, 2024

2023

Jump Interval-Learning for Individualized Decision Making with Continuous Treatments.

Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu

J. Mach. Learn. Res., 2023

Robust Offline Policy Evaluation and Optimization with Heavy-Tailed Rewards.

Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi

CoRR, 2023

Off-policy Evaluation in Doubly Inhomogeneous Environments.

Zeyu Bian, Chengchun Shi, Zhengling Qi, Lan Wang

CoRR, 2023

Testing for the Markov Property in Time Series via Deep Conditional Generative Learning.

Yunzhe Zhou, Chengchun Shi, Lexin Li, Qiwei Yao

CoRR, 2023

Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing.

Ting Li, Chengchun Shi, Zhaohua Lu, Yi Li, Hongtu Zhu

CoRR, 2023

Sequential Knockoffs for Variable Selection in Reinforcement Learning.

Tao Ma, Hengrui Cai, Zhengling Qi, Chengchun Shi, Eric B. Laber

CoRR, 2023

Value Enhancement of Reinforcement Learning via Efficient and Robust Trust Region Optimization.

Chengchun Shi, Zhengling Qi, Jianing Wang, Fan Zhou

CoRR, 2023

Deep Spectral Q-learning with Application to Mobile Health.

Yuhe Gao, Chengchun Shi, Rui Song

CoRR, 2023

Future-Dependent Value-Based Off-Policy Evaluation in POMDPs.

Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making.

Ting Li, Chengchun Shi, Jianing Wang, Fan Zhou, Hongtu Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DNet: Distributional Network for Distributional Individualized Treatment Effects.

Guojun Wu, Ge Song, Xiaoxiang Lv, Shikai Luo, Chengchun Shi, Hongtu Zhu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

An Instrumental Variable Approach to Confounded Off-Policy Evaluation.

Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song

Proceedings of the International Conference on Machine Learning, 2023

A Robust Test for the Stationarity Assumption in Sequential Decision Making.

Jitao Wang, Chengchun Shi, Zhenke Wu

Proceedings of the International Conference on Machine Learning, 2023

A Reinforcement Learning Framework for Dynamic Mediation Analysis.

Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song

Proceedings of the International Conference on Machine Learning, 2023

Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach.

Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Conformal Off-Policy Prediction.

Yingying Zhang, Chengchun Shi, Shikai Luo

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Quantile Off-Policy Evaluation via Deep Conditional Generative Learning.

Yang Xu, Chengchun Shi, Shikai Luo, Lan Wang, Rui Song

CoRR, 2022

A Review of Off-Policy Evaluation in Reinforcement Learning.

Masatoshi Uehara, Chengchun Shi, Nathan Kallus

CoRR, 2022

Doubly Inhomogeneous Reinforcement Learning.

Liyuan Hu, Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz

CoRR, 2022

Blessing from Experts: Super Reinforcement Learning in Confounded Environments.

Jiayi Wang, Zhengling Qi, Chengchun Shi

CoRR, 2022

Reinforcement Learning in Possibly Nonstationary Environments.

Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz

CoRR, 2022

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons.

Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song

CoRR, 2022

Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms.

Shikai Luo, Ying Yang, Chengchun Shi, Fang Yao, Jieping Ye, Hongtu Zhu

CoRR, 2022

Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process.

Chengchun Shi, Jin Zhu, Ye Shen, Shikai Luo, Hongtu Zhu, Rui Song

CoRR, 2022

A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets.

Chengchun Shi, Runzhe Wan, Ge Song, Shikai Luo, Rui Song, Hongtu Zhu

CoRR, 2022

A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes.

Chengchun Shi, Masatoshi Uehara, Jiawei Huang, Nan Jiang

Proceedings of the International Conference on Machine Learning, 2022

2021

Double Generative Adversarial Networks for Conditional Independence Testing.

Chengchun Shi, Tianlin Xu, Wicher Bergsma, Lexin Li

J. Mach. Learn. Res., 2021

An Online Sequential Test for Qualitative Treatment Effects.

Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song

J. Mach. Learn. Res., 2021

Jump Interval-Learning for Individualized Decision Making.

Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu

CoRR, 2021

A Minimax Learning Approach to Off-Policy Evaluation in Partially Observable Markov Decision Processes.

Chengchun Shi, Masatoshi Uehara, Nan Jiang

CoRR, 2021

Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning.

Chengchun Shi, Yunzhe Zhou, Lexin Li

CoRR, 2021

Pattern Transfer Learning for Reinforcement Learning in Order Dispatching.

Runzhe Wan, Sheng Zhang, Chengchun Shi, Shikai Luo, Rui Song

CoRR, 2021

Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings.

Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deeply-Debiased Off-Policy Interval Estimation.

Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Breaking the Curse of Nonregularity with Subagging - Inference of the Mean Outcome under Optimal Treatment Regimes.

Chengchun Shi, Wenbin Lu, Rui Song

J. Mach. Learn. Res., 2020

Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space.

Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu

CoRR, 2020

A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing.

Chengchun Shi, Xiaoyu Wang, Shikai Luo, Rui Song, Hongtu Zhu, Jieping Ye

CoRR, 2020

Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings.

Chengchun Shi, Sheng Zhang, Wenbin Lu, Rui Song

CoRR, 2020

Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making.

Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Determining the Number of Latent Factors in Statistical Multi-Relational Learning.

Chengchun Shi, Wenbin Lu, Rui Song

J. Mach. Learn. Res., 2019