Integrative prescreening in analysis of multiple cancer genomic studies. - Rui Song 006; Jian Huang 003; Shuangge Ma (BMC Bioinform., 2012)

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

Principal components adjusted variable screening. - Zhongkai Liu; Rui Song 006; Donglin Zeng; Jiajia Zhang (Comput. Stat. Data Anal., 2017)

Sparse Concordance-assisted Learning for Optimal Treatment Decision. - Shuhan Liang; Wenbin Lu; Rui Song 006; Lan Wang (J. Mach. Learn. Res., 2017)

Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach. - Menghai Pan; Yanhua Li; Xun Zhou 001; Zhenming Liu; Rui Song 006; Hui Lu 005; Jun Luo 007 (SDM, 2019)

Determining the Number of Latent Factors in Statistical Multi-Relational Learning. - Chengchun Shi; Wenbin Lu; Rui Song 006 (J. Mach. Learn. Res., 2019)

A New Framework for Online Testing of Heterogeneous Treatment Effect. - Miao Yu; Wenbin Lu; Rui Song 006 (AAAI, 2020)

Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning. - Ye Liu; Sheng Zhang 027; Rui Song 006; Suo Feng; Yanghua Xiao (EMNLP (1), 2020)

On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies. - Hengrui Cai; Wenbin Lu; Rui Song 006 (ICML, 2020)

Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. - Chengchun Shi; Runzhe Wan; Rui Song 006; Wenbin Lu; Ling Leng (ICML, 2020)

Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health. - Liangyu Zhu; Wenbin Lu; Rui Song 006 (ICML, 2020)

Kernel Assisted Learning for Personalized Dose Finding. - Liangyu Zhu; Wenbin Lu; Michael R. Kosorok; Rui Song 006 (KDD, 2020)

Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings. - Chengchun Shi; Sheng Zhang 027; Wenbin Lu; Rui Song 006 (CoRR, 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)

Multi-Objective Reinforcement Learning for Infectious Disease Control with Application to COVID-19 Spread. - Runzhe Wan; Xinyu Zhang; Rui Song 006 (CoRR, 2020)

Statistical Inference for Online Decision-Making: In a Contextual Bandit Setting. - Haoyu Chen; Wenbin Lu; Rui Song 006 (CoRR, 2020)

Statistical Inference for Online Decision Making via Stochastic Gradient Descent. - Haoyu Chen; Wenbin Lu; Rui Song 006 (CoRR, 2020)

Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (CoRR, 2020)

Breaking the Curse of Nonregularity with Subagging - Inference of the Mean Outcome under Optimal Treatment Regimes. - Chengchun Shi; Wenbin Lu; Rui Song 006 (J. Mach. Learn. Res., 2020)

DHPA: Dynamic Human Preference Analytics Framework: A Case Study on Taxi Drivers' Learning Curve Analysis. - Menghai Pan; Weixiao Huang; Yanhua Li; Xun Zhou 001; Zhenming Liu; Rui Song 006; Hui Lu 005; Zhihong Tian; Jun Luo 007 (ACM Trans. Intell. Syst. Technol., 2020)

Online Testing of Subgroup Treatment Effects Based on Value Difference. - Miao Yu; Wenbin Lu; Rui Song 006 (ICDM, 2021)

ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning. - Hengrui Cai; Rui Song 006; Wenbin Lu (ICLR, 2021)

Deeply-Debiased Off-Policy Interval Estimation. - Chengchun Shi; Runzhe Wan; Victor Chernozhukov; Rui Song 006 (ICML, 2021)

Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control. - Runzhe Wan; Xinyu Zhang; Rui Song 006 (KDD, 2021)

Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (NeurIPS, 2021)

Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models. - Runzhe Wan; Lin Ge; Rui Song 006 (NeurIPS, 2021)

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

Periodic-GP: Learning Periodic World with Gaussian Process Bandits. - Hengrui Cai; Zhihao Cen; Ling Leng; Rui Song 006 (CoRR, 2021)

Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning. - Hengrui Cai; Ye Shen; Rui Song 006 (CoRR, 2021)

Jump Interval-Learning for Individualized Decision Making. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (CoRR, 2021)

A Review on Graph Neural Network Methods in Financial Applications. - Jianian Wang; Sheng Zhang 027; Yanghua Xiao; 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)

Crossword Puzzle Resolution via Monte Carlo Tree Search. - Lihan Chen; Jingping Liu; Sihang Jiang; Chao Wang 095; Jiaqing Liang; Yanghua Xiao; Sheng Zhang 027; Rui Song 006 (ICAPS, 2022)

Safe Exploration for Efficient Policy Evaluation and Comparison. - Runzhe Wan; Branislav Kveton; Rui Song 006 (ICML, 2022)

Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond. - Zhiwei (Tony) Qin; Liangjie Hong; Rui Song 006; Hongtu Zhu; Mohammed Korayem; Haiyan Luo; Michael I. Jordan (KDD, 2022)

Reinforcement Learning with Heterogeneous Data: Estimation and Inference. - Elynn Y. Chen; Rui Song 006; Michael I. Jordan (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 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)

On Learning and Testing of Counterfactual Fairness through Data Preprocessing. - Haoyu Chen; Wenbin Lu; Rui Song 006; Pulak Ghosh (CoRR, 2022)

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

Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies. - Runzhe Wan; Yingying Li; Wenbin Lu; 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)

Heterogeneous Synthetic Learner for Panel Data. - Ye Shen; Runzhe Wan; Hengrui Cai; Rui Song 006 (CoRR, 2022)

Rule mining over knowledge graphs via reinforcement learning. - Lihan Chen; Sihang Jiang; Jingping Liu; Chao Wang 095; Sheng Zhang 027; Chenhao Xie 002; Jiaqing Liang; Yanghua Xiao; Rui Song 006 (Knowl. Based Syst., 2022)

Learning a deep dual-level network for robust DeepFake detection. - Wenbo Pu; Jing Hu 009; Xin Wang 045; Yuezun Li; Shu Hu 001; Bin Zhu 008; Rui Song 006; Qi Song 001; Xi Wu 004; Siwei Lyu (Pattern Recognit., 2022)

KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond. - Zhiwei (Tony) Qin; Liangjie Hong; Rui Song 006; Hongtu Zhu; Mohammed Korayem; Haiyan Luo; Michael I. Jordan (SIGKDD Explor., 2022)

A Probit Tensor Factorization Model For Relational Learning. - Ye Liu; Rui Song 006; Wenbin Lu; Yanghua Xiao (J. Comput. Graph. Stat., 2022)

Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework. - Runzhe Wan; Lin Ge; Rui Song 006 (AISTATS, 2023)

A Reinforcement Learning Framework for Dynamic Mediation Analysis. - Lin Ge; Jitao Wang; Chengchun Shi; Zhenke Wu; Rui Song 006 (ICML, 2023)

Multiplier Bootstrap-based Exploration. - Runzhe Wan; Haoyu Wei; Branislav Kveton; Rui Song 006 (ICML, 2023)

On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs. - Richard A. Watson; Hengrui Cai; Xinming An; Samuel A. McLean; Rui Song 006 (ICML, 2023)

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

KDD-2023 Workshop on Decision Intelligence and Analytics for Online Marketplaces. - Zhiwei (Tony) Qin; Rui Song 006; Jieping Ye; Hongtu Zhu; Michael I. Jordan (KDD, 2023)

Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. - Runzhe Wan; Yu Liu 080; James McQueen; Doug Hains; Rui Song 006 (KDD, 2023)

On Learning Necessary and Sufficient Causal Graphs. - Hengrui Cai; Yixin Wang 002; Michael I. Jordan; Rui Song 006 (NeurIPS, 2023)

Deep Spectral Q-learning with Application to Mobile Health. - Yuhe Gao; Chengchun Shi; Rui Song 006 (CoRR, 2023)

Zero-Inflated Bandits. - Haoyu Wei; Runzhe Wan; Lei Shi; Rui Song 006 (CoRR, 2023)

Large Language Model for Causal Decision Making. - Haitao Jiang; Lin Ge; Yuhe Gao; Jianian Wang; Rui Song 006 (CoRR, 2023)

Jump Interval-Learning for Individualized Decision Making with Continuous Treatments. - Hengrui Cai; Chengchun Shi; Rui Song 006; Wenbin Lu (J. Mach. Learn. Res., 2023)

Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches. - Yu Liu 080; Runzhe Wan; James McQueen; Doug Hains; Jinxiang Gu; Rui Song 006 (AAAI, 2024)

Online Posterior Sampling with a Diffusion Prior. - Branislav Kveton; Boris Oreshkin; Youngsuk Park; Aniket Deshmukh 001; Rui Song 006 (NeurIPS, 2024)

A crossword solving system based on Monte Carlo tree search. - Jingping Liu; Lihan Chen; Sihang Jiang; Chao Wang 095; Sheng Zhang 027; Jiaqing Liang; Yanghua Xiao; Rui Song 006 (Artif. Intell., 2024)

Is Knowledge All Large Language Models Needed for Causal Reasoning? - Hengrui Cai; Shengjie Liu; Rui Song 006 (CoRR, 2024)

Linear Contextual Bandits with Interference. - Yang Xu; Wenbin Lu; Rui Song 006 (CoRR, 2024)

A Review of Reinforcement Learning in Financial Applications. - Yahui Bai; Yuhe Gao; Runzhe Wan; Sheng Zhang 027; Rui Song 006 (CoRR, 2024)

Multi-Task Combinatorial Bandits for Budget Allocation. - Lin Ge; Yang Xu; Jianing Chu; David Cramer; Fuhong Li; Kelly Paulson; Rui Song 006 (KDD (1), 2025)

Dynamic Causal Structure Discovery and Causal Effect Estimation. - Jianian Wang; Rui Song 006 (KDD (1), 2025)

Know When to Fold: Futility-Aware Early Termination in Online Experiments. - Yu Liu 080; Runzhe Wan; Yian Huang; James McQueen; Doug Hains; Jinxiang Gu; Rui Song 006 (WWW (Companion Volume), 2025)

A Review of Causal Decision Making. - Lin Ge; Hengrui Cai; Runzhe Wan; Yang Xu; Rui Song 006 (CoRR, 2025)

Continuous-Time Hidden Markov Factor Model for Mobile Health Data: Application to Adverse Posttraumatic Neuropsychiatric Sequelae. - Lin Ge; Xinming An; Donglin Zeng; Samuel A. McLean; Ronald C. Kessler; Rui Song 006 (IEEE J. Biomed. Health Informatics, 2025)

Off-Policy Evaluation Under Nonignorable Missing Data. - Han Wang; Yang Xu; Wenbin Lu; Rui Song 006 (CoRR, 2025)