Chengchun Shi - RankMe

85 papers A* 16A 3B 1Journal 65

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Difference-in-Difference Approach to Detecting AI-Generated Images. CoRR Xinyi Qi, Kai Ye, Chengchun Shi, Ying Yang, Hongyi Zhou, Jin Zhu
2026	J	`jnl`	Demystifying Group Relative Policy Optimization: Its Policy Gradient is a U-Statistic. CoRR Hongyi Zhou, Kai Ye, Erhan Xu, Jin Zhu, Ying Yang, Shijin Gong, Chengchun Shi
2026	J	`jnl`	Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning. CoRR Xiangkun Wu, Qianglin Wen, Yingying Zhang, Hongtu Zhu, Ting Li, Chengchun Shi
2026	J	`jnl`	Detecting LLM-Generated Text with Performance Guarantees. CoRR Hongyi Zhou, Jin Zhu, Ying Yang, Chengchun Shi
2026	J	`jnl`	Double Fairness Policy Learning: Integrating Action Fairness and Outcome Fairness in Decision-making. CoRR Zeyu Bian, Lan Wang, Chengchun Shi, Zhengling Qi
2026	J	`jnl`	Learn-to-Distance: Distance Learning for Detecting LLM-Generated Text. CoRR Hongyi Zhou, Jin Zhu, Erhan Xu, Kai Ye, Ying Yang, Chengchun Shi
2025	J	`jnl`	A Two-armed Bandit Framework for A/B Testing. CoRR Jinjuan Wang, Qianglin Wen, Yu Zhang, Xiaodong Yan, Chengchun Shi
2025	J	`jnl`	AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees. CoRR Hongyi Zhou, Jin Zhu, Pingfan Su, Kai Ye, Ying Yang, Shakeel A O. B. Gavioli-Akilagun, Chengchun Shi
2025	A*	`conf`	Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach. ICML Jin Zhu, Jingyi Li, Hongyi Zhou, Yinan Lin, Zhenhua Lin, Chengchun Shi
2025	J	`jnl`	Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach. CoRR Zhu Jin, Jingyi Li, Hongyi Zhou, Yinan Lin, Zhenhua Lin, Chengchun Shi
2025	J	`jnl`	Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing. CoRR Jitao Wang, Chengchun Shi, John D. Piette, Joshua R. Loftus, Donglin Zeng, Zhenke Wu
2025	J	`jnl`	Deep Distributional Learning with Non-crossing Quantile Network. CoRR Guohao Shen, Runpeng Dai, Guojun Wu, Shikai Luo, Chengchun Shi, Hongtu Zhu
2025	A*	`conf`	Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation. ICML Hongyi Zhou, Josiah P. Hanna, Jin Zhu, Ying Yang, Chengchun Shi
2025	J	`jnl`	Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation. CoRR Hongyi Zhou, Josiah P. Hanna, Jin Zhu, Ying Yang, Chengchun Shi
2025	J	`jnl`	Doubly Robust Alignment for Large Language Models. CoRR Erhan Xu, Kai Ye, Hongyi Zhou, Luhan Zhu, Francesco Quinzan, Chengchun Shi
2025	J	`jnl`	Doubly Robust Uncertainty Quantification for Quantile Treatment Effects in Sequential Decision Making. Trans. Mach. Learn. Res. Yang Xu, Chengchun Shi, Shikai Luo, Lan Wang, Rui Song
2025	J	`jnl`	From Authors to Reviewers: Leveraging Rankings to Improve Peer Review. CoRR Weichen Wang, Chengchun Shi
2025	J	`jnl`	Generalized Fitted Q-Iteration with Clustered Data. CoRR Liyuan Hu, Jitao Wang, Zhenke Wu, Chengchun Shi
2025	A*	`conf`	Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning. ICML Armin Behnamnia, Gholamali Aminian, Alireza Aghaei, Chengchun Shi, Vincent Y. F. Tan, Hamid R. Rabiee
2025	J	`jnl`	Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning. CoRR Armin Behnamnia, Gholamali Aminian, Alireza Aghaei, Chengchun Shi, Vincent Y. F. Tan, Hamid R. Rabiee
2025	J	`jnl`	Optimized SVR model for predicting dissolved oxygen levels using wavelet denoising and variable reduction: Taking the Minjiang River estuary as an example. Ecol. Informatics Peng Zhang, Xinyang Liu, Huiru Zhang, Chengchun Shi, Gangfu Song, Lei Tang, Ruihua Li
2025	J	`jnl`	PyCFRL: A Python library for counterfactually fair offline reinforcement learning via sequential data preprocessing. CoRR Jianhan Zhang, Jitao Wang, Chengchun Shi, John D. Piette, Donglin Zeng, Zhenke Wu
2025	J	`jnl`	ReDiF: Reinforced Distillation for Few Step Diffusion. CoRR Amirhossein Tighkhorshid, Zahra Dehghanian, Gholamali Aminian, Chengchun Shi, Hamid R. Rabiee
2025	J	`jnl`	Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning. CoRR Kai Ye, Hongyi Zhou, Jin Zhu, Francesco Quinzan, Chengchun Shi
2025	J	`jnl`	Semi-pessimistic Reinforcement Learning. CoRR Jin Zhu, Xin Zhou, Jiaang Yao, Gholamali Aminian, Omar Rivasplata, Simon Little, Lexin Li, Chengchun Shi
2025	J	`jnl`	Statistical Inference in Reinforcement Learning: A Selective Survey. CoRR Chengchun Shi
2025	A*	`conf`	Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments. ICML Qianglin Wen, Chengchun Shi, Ying Yang, Niansheng Tang, Hongtu Zhu
2024	J	`jnl`	Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferences. CoRR Runpeng Dai, Jianing Wang, Fan Zhou, Shikai Luo, Zhiwei Qin, Chengchun Shi, Hongtu Zhu
2024	A*	`conf`	Combining Experimental and Historical Data for Policy Evaluation. ICML Ting Li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin, Chunbo Lai, Hongtu Zhu
2024	J	`jnl`	Combining Experimental and Historical Data for Policy Evaluation. CoRR Ting Li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin, Chunbo Lai, Hongtu Zhu
2024	J	`jnl`	Dual Active Learning for Reinforcement Learning from Human Feedback. CoRR Pangpang Liu, Chengchun Shi, Will Wei Sun
2024	J	`jnl`	Forward and Backward State Abstractions for Off-policy Evaluation. CoRR Meiling Hao, Pingfan Su, Liyuan Hu, Zoltan Szabo, Qingyuan Zhao, Chengchun Shi
2024	J	`jnl`	Pessimistic Causal Reinforcement Learning with Mediators for Confounded Offline Data. CoRR Danyang Wang, Chengchun Shi, Shikai Luo, Will Wei Sun
2024	A	`conf`	Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. AISTATS Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi
2024	A*	`conf`	Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning. NeurIPS Shuguang Yu, Shuxing Fang, Ruixin Peng, Zhengling Qi, Fan Zhou, Chengchun Shi
2024	J	`jnl`	Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning. CoRR Shuguang Yu, Shuxing Fang, Ruixin Peng, Zhengling Qi, Fan Zhou, Chengchun Shi
2023	A*	`conf`	A Reinforcement Learning Framework for Dynamic Mediation Analysis. ICML Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song
2023	J	`jnl`	A Reinforcement Learning Framework for Dynamic Mediation Analysis. CoRR Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song
2023	A*	`conf`	A Robust Test for the Stationarity Assumption in Sequential Decision Making. ICML Jitao Wang, Chengchun Shi, Zhenke Wu
2023	B	`conf`	A generalized method for dynamic noise inference in modeling sequential decision-making. CogSci Jing-Jing Li, Chengchun Shi, Lexin Li, Anne G. E. Collins
2023	A*	`conf`	An Instrumental Variable Approach to Confounded Off-Policy Evaluation. ICML Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song
2023	A	`conf`	Conformal Off-Policy Prediction. AISTATS Yingying Zhang, Chengchun Shi, Shikai Luo
2023	A*	`conf`	DNet: Distributional Network for Distributional Individualized Treatment Effects. KDD Guojun Wu, Ge Song, Xiaoxiang Lv, Shikai Luo, Chengchun Shi, Hongtu Zhu
2023	J	`jnl`	Deep Spectral Q-learning with Application to Mobile Health. CoRR Yuhe Gao, Chengchun Shi, Rui Song
2023	J	`jnl`	Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing. CoRR Ting Li, Chengchun Shi, Zhaohua Lu, Yi Li, Hongtu Zhu
2023	A*	`conf`	Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. NeurIPS Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
2023	J	`jnl`	Jump Interval-Learning for Individualized Decision Making with Continuous Treatments. J. Mach. Learn. Res. Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
2023	J	`jnl`	Off-policy Evaluation in Doubly Inhomogeneous Environments. CoRR Zeyu Bian, Chengchun Shi, Zhengling Qi, Lan Wang
2023	A*	`conf`	Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making. NeurIPS Ting Li, Chengchun Shi, Jianing Wang, Fan Zhou, Hongtu Zhu
2023	A	`conf`	Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. AISTATS Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li
2023	J	`jnl`	Robust Offline Policy Evaluation and Optimization with Heavy-Tailed Rewards. CoRR Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi
2023	J	`jnl`	Sequential Knockoffs for Variable Selection in Reinforcement Learning. CoRR Tao Ma, Hengrui Cai, Zhengling Qi, Chengchun Shi, Eric B. Laber
2023	J	`jnl`	Testing for the Markov Property in Time Series via Deep Conditional Generative Learning. CoRR Yunzhe Zhou, Chengchun Shi, Lexin Li, Qiwei Yao
2023	J	`jnl`	Value Enhancement of Reinforcement Learning via Efficient and Robust Trust Region Optimization. CoRR Chengchun Shi, Zhengling Qi, Jianing Wang, Fan Zhou
2022	A*	`conf`	A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes. ICML Chengchun Shi, Masatoshi Uehara, Jiawei Huang, Nan Jiang
2022	J	`jnl`	A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets. CoRR Chengchun Shi, Runzhe Wan, Ge Song, Shikai Luo, Rui Song, Hongtu Zhu
2022	J	`jnl`	A Review of Off-Policy Evaluation in Reinforcement Learning. CoRR Masatoshi Uehara, Chengchun Shi, Nathan Kallus
2022	J	`jnl`	An Instrumental Variable Approach to Confounded Off-Policy Evaluation. CoRR Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song
2022	J	`jnl`	Blessing from Experts: Super Reinforcement Learning in Confounded Environments. CoRR Jiayi Wang, Zhengling Qi, Chengchun Shi
2022	J	`jnl`	Conformal Off-Policy Prediction. CoRR Yingying Zhang, Chengchun Shi, Shikai Luo
2022	J	`jnl`	Doubly Inhomogeneous Reinforcement Learning. CoRR Liyuan Hu, Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz
2022	J	`jnl`	Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. CoRR Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
2022	J	`jnl`	Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process. CoRR Chengchun Shi, Jin Zhu, Ye Shen, Shikai Luo, Hongtu Zhu, Rui Song
2022	J	`jnl`	Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. CoRR Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li
2022	J	`jnl`	Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms. CoRR Shikai Luo, Ying Yang, Chengchun Shi, Fang Yao, Jieping Ye, Hongtu Zhu
2022	J	`jnl`	Quantile Off-Policy Evaluation via Deep Conditional Generative Learning. CoRR Yang Xu, Chengchun Shi, Shikai Luo, Lan Wang, Rui Song
2022	J	`jnl`	Reinforcement Learning in Possibly Nonstationary Environments. CoRR Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz
2022	J	`jnl`	Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons. CoRR Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song
2021	J	`jnl`	A Minimax Learning Approach to Off-Policy Evaluation in Partially Observable Markov Decision Processes. CoRR Chengchun Shi, Masatoshi Uehara, Nan Jiang
2021	J	`jnl`	An Online Sequential Test for Qualitative Treatment Effects. J. Mach. Learn. Res. Chengchun Shi, Shikai Luo, Hongtu Zhu, Rui Song
2021	A*	`conf`	Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. NeurIPS Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
2021	A*	`conf`	Deeply-Debiased Off-Policy Interval Estimation. ICML Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
2021	J	`jnl`	Deeply-Debiased Off-Policy Interval Estimation. CoRR Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
2021	J	`jnl`	Double Generative Adversarial Networks for Conditional Independence Testing. J. Mach. Learn. Res. Chengchun Shi, Tianlin Xu, Wicher Bergsma, Lexin Li
2021	J	`jnl`	Jump Interval-Learning for Individualized Decision Making. CoRR Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
2021	J	`jnl`	Pattern Transfer Learning for Reinforcement Learning in Order Dispatching. CoRR Runzhe Wan, Sheng Zhang, Chengchun Shi, Shikai Luo, Rui Song
2021	J	`jnl`	Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning. CoRR Chengchun Shi, Yunzhe Zhou, Lexin Li
2020	J	`jnl`	A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing. CoRR Chengchun Shi, Xiaoyu Wang, Shikai Luo, Rui Song, Hongtu Zhu, Jieping Ye
2020	J	`jnl`	Breaking the Curse of Nonregularity with Subagging - Inference of the Mean Outcome under Optimal Treatment Regimes. J. Mach. Learn. Res. Chengchun Shi, Wenbin Lu, Rui Song
2020	J	`jnl`	Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space. CoRR Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
2020	A*	`conf`	Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. ICML Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
2020	J	`jnl`	Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. CoRR Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
2020	J	`jnl`	Double Generative Adversarial Networks for Conditional Independence Testing. CoRR Chengchun Shi, Tianlin Xu, Wicher Bergsma, Lexin Li
2020	J	`jnl`	Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings. CoRR Chengchun Shi, Sheng Zhang, Wenbin Lu, Rui Song
2019	J	`jnl`	Determining the Number of Latent Factors in Statistical Multi-Relational Learning. J. Mach. Learn. Res. Chengchun Shi, Wenbin Lu, Rui Song