Multivariate and Categorical Analysis of Gaming Statistics. - Pin-Yu Chen; Zhengling Qi; Yanxin Pan; Shin-Ming Cheng (NBiS, 2015)

Statistical Analysis of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization. - Zhengling Qi; Ying Cui 004; Yufeng Liu; Jong-Shi Pang (CoRR, 2019)

How Mega Is the Mega? Exploring the Spillover Effects of WeChat Using Graphical Model. - Jinyang Zheng; Zhengling Qi; Yifan Dou; Yong Tan (Inf. Syst. Res., 2019)

Estimation of Individualized Decision Rules Based on an Optimized Covariate-Dependent Equivalent of Random Outcomes. - Zhengling Qi; Ying Cui 004; Yufeng Liu; Jong-Shi Pang (SIAM J. Optim., 2019)

Convex Bidirectional Large Margin Classifiers. - Zhengling Qi; Yufeng Liu (Technometrics, 2019)

Some Contributions to Data Driven Individualized Decision Making Problems. - Zhengling Qi (2019)

Learning Optimal Distributionally Robust Individualized Treatment Rules. - Weibin Mo; Zhengling Qi; Yufeng Liu (CoRR, 2020)

Robust Batch Policy Learning in Markov Decision Processes. - Zhengling Qi; Peng Liao (CoRR, 2020)

Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding. - Zhengling Qi; Rui Miao; Xiaoke Zhang (CoRR, 2021)

Projected State-action Balancing Weights for Offline Reinforcement Learning. - Jiayi Wang; Zhengling Qi; Raymond K. W. Wong (CoRR, 2021)

Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules. - Weibin Mo; Zhengling Qi; Yufeng Liu (CoRR, 2021)

On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation. - Xiaohong Chen; Zhengling Qi (ICML, 2022)

Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models. - Rui Miao; Zhengling Qi; Xiaoke Zhang (NeurIPS, 2022)

RISE: Robust Individualized Decision Learning with Sensitive Variables. - Xiaoqing Tan; Zhengling Qi; Christopher W. Seymour; Lu Tang 003 (NeurIPS, 2022)

Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes. - Zuyue Fu; Zhengling Qi; Zhaoran Wang 001; Zhuoran Yang; Yanxun Xu; Michael R. Kosorok (CoRR, 2022)

Blessing from Experts: Super Reinforcement Learning in Confounded Environments. - Jiayi Wang; Zhengling Qi; Chengchun Shi (CoRR, 2022)

Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information. - Zuyue Fu; Zhengling Qi; Zhuoran Yang; Zhaoran Wang 001; Lan Wang (CoRR, 2022)

Asymptotic Properties of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization. - Zhengling Qi; Ying Cui 004; Yufeng Liu; Jong-Shi Pang (Math. Oper. Res., 2022)

Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. - Yunzhe Zhou; Zhengling Qi; Chengchun Shi; Lexin Li (AISTATS, 2023)

PASTA: Pessimistic Assortment Optimization. - Juncheng Dong; Weibin Mo; Zhengling Qi; Cong Shi 001; Ethan X. Fang; Vahid Tarokh (ICML, 2023)

Pessimistic Model Selection for Offline Deep Reinforcement Learning. - Chao-Han Huck Yang; Zhengling Qi; Yifan Cui 001; Pin-Yu Chen (UAI, 2023)

Value Enhancement of Reinforcement Learning via Efficient and Robust Trust Region Optimization. - Chengchun Shi; Zhengling Qi; Jianing Wang; Fan Zhou (CoRR, 2023)

STEEL: Singularity-aware Reinforcement Learning. - Xiaohong Chen; Zhengling Qi; Runzhe Wan (CoRR, 2023)

Personalized Pricing with Invalid Instrumental Variables: Identification, Estimation, and Policy Learning. - Rui Miao; Zhengling Qi; Cong Shi 001; Lin Lin (CoRR, 2023)

Sequential Knockoffs for Variable Selection in Reinforcement Learning. - Tao Ma; Hengrui Cai; Zhengling Qi; Chengchun Shi; Eric B. Laber (CoRR, 2023)

Off-policy Evaluation in Doubly Inhomogeneous Environments. - Zeyu Bian; Chengchun Shi; Zhengling Qi; Lan Wang (CoRR, 2023)

Robust Offline Policy Evaluation and Optimization with Heavy-Tailed Rewards. - Jin Zhu; Runzhe Wan; Zhengling Qi; Shikai Luo; Chengchun Shi (CoRR, 2023)

Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. - Jin Zhu; Runzhe Wan; Zhengling Qi; Shikai Luo; Chengchun Shi (AISTATS, 2024)

A Policy Gradient Method for Confounded POMDPs. - Mao Hong; Zhengling Qi; Yanxun Xu (ICLR, 2024)

Model-based Reinforcement Learning for Confounded POMDPs. - Mao Hong; Zhengling Qi; Yanxun Xu (ICML, 2024)

A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models. - Jiayi Wang; Zhengling Qi; Raymond K. W. Wong (ICML, 2024)

Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning. - Shuguang Yu; Shuxing Fang; Ruixin Peng; Zhengling Qi; Fan Zhou; Chengchun Shi (NeurIPS, 2024)

A Tale of Two Cities: Pessimism and Opportunism in Offline Dynamic Pricing. - Zeyu Bian; Zhengling Qi; Cong Shi 001; Lan Wang (CoRR, 2024)

Distributional Off-policy Evaluation with Bellman Residual Minimization. - Sungee Hong; Zhengling Qi; Raymond K. W. Wong (AISTATS, 2025)

Offline Feature-Based Pricing Under Censored Demand: A Causal Inference Approach. - Jingwen Tang; Zhengling Qi; Ethan X. Fang; Cong Shi 001 (Manuf. Serv. Oper. Manag., 2025)

Offline Dynamic Inventory and Pricing Strategy: Addressing Censored and Dependent Demand. - Korel Gundem; Zhengling Qi (CoRR, 2025)

Reinforcement Learning with Continuous Actions Under Unmeasured Confounding. - Yuhan Li; Eugene Han; Yifan Hu; Wenzhuo Zhou; Zhengling Qi; Yifan Cui 001; Ruoqing Zhu (CoRR, 2025)

Boosting In-Context Learning in LLMs Through the Lens of Classical Supervised Learning. - Korel Gundem; Juncheng Dong; Dennis Zhang; Vahid Tarokh; Zhengling Qi (CoRR, 2025)

Quantile-Optimal Policy Learning under Unmeasured Confounding. - Zhongren Chen; Siyu Chen; Zhengling Qi; Xiaohong Chen; Zhuoran Yang (CoRR, 2025)

A Principled Path to Fitted Distributional Evaluation. - Sungee Hong; Jiayi Wang; Zhengling Qi; Raymond K. W. Wong (CoRR, 2025)

POLAR: A Pessimistic Model-based Policy Learning Algorithm for Dynamic Treatment Regimes. - Ruijia Zhang; Zhengling Qi; Yue Wu; Xiangyu Zhang; Yanxun Xu (CoRR, 2025)