Sure Screening for Gaussian Graphical Models. - Shikai Luo; Rui Song 006; Daniela M. Witten (CoRR, 2014)

Quantitative tract-based white matter heritability in twin neonates. - Seung Jae Lee; Rachel J. Steiner; Shikai Luo; Michael C. Neale; Martin Styner; Hongtu Zhu; John H. Gilmore (NeuroImage, 2015)

A Joint Inverse Reinforcement Learning and Deep Learning Model for Drivers' Behavioral Prediction. - Guojun Wu; Yanhua Li; Shikai Luo; Ge Song; Qichao Wang; Jing He; Jieping Ye; Xiaohu Qie; Hongtu Zhu (CIKM, 2020)

A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing. - Chengchun Shi; Xiaoyu Wang; Shikai Luo; Rui Song 006; Hongtu Zhu; Jieping Ye (CoRR, 2020)

Pattern Transfer Learning for Reinforcement Learning in Order Dispatching. - Runzhe Wan; Sheng Zhang 027; Chengchun Shi; Shikai Luo; Rui Song 006 (CoRR, 2021)

An Online Sequential Test for Qualitative Treatment Effects. - Chengchun Shi; Shikai Luo; Hongtu Zhu; Rui Song 006 (J. Mach. Learn. Res., 2021)

A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets. - Chengchun Shi; Runzhe Wan; Ge Song; Shikai Luo; Rui Song 006; 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 006 (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)

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons. - Chengchun Shi; Shikai Luo; Hongtu Zhu; Rui Song 006 (CoRR, 2022)

Quantile Off-Policy Evaluation via Deep Conditional Generative Learning. - Yang Xu; Chengchun Shi; Shikai Luo; Lan Wang; Rui Song 006 (CoRR, 2022)

Conformal Off-Policy Prediction. - Yingying Zhang; Chengchun Shi; Shikai Luo (AISTATS, 2023)

An Instrumental Variable Approach to Confounded Off-Policy Evaluation. - Yang Xu; Jin Zhu; Chengchun Shi; Shikai Luo; Rui Song 006 (ICML, 2023)

DNet: Distributional Network for Distributional Individualized Treatment Effects. - Guojun Wu; Ge Song; Xiaoxiang Lv; Shikai Luo; Chengchun Shi; Hongtu Zhu (KDD, 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)

Pessimistic Causal Reinforcement Learning with Mediators for Confounded Offline Data. - Danyang Wang; Chengchun Shi; Shikai Luo; Will Wei Sun (CoRR, 2024)

Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferences. - Runpeng Dai; Jianing Wang; Fan Zhou; Shikai Luo; Zhiwei Qin; Chengchun Shi; Hongtu Zhu (CoRR, 2024)

Causal Probabilistic Spatio-Temporal Fusion Transformers in Two-Sided Ride-Hailing Markets. - Shixiang Wan; Shikai Luo; Hongtu Zhu (ACM Trans. Spatial Algorithms Syst., 2024)

Deep Distributional Learning with Non-crossing Quantile Network. - Guohao Shen; Runpeng Dai; Guojun Wu; Shikai Luo; Chengchun Shi; Hongtu Zhu (CoRR, 2025)