Runzhe Wan

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 26

Top Topics

Interval Estimation

Reinforcement Learning

Infectious Disease

Markov Decision Processes

Top Venues

Publications

Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi
Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. AISTATS (2024)
Yu Liu, Runzhe Wan, James McQueen, Doug Hains, Jinxiang Gu, Rui Song
Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches. AAAI (2024)
Runzhe Wan, Lin Ge, Rui Song
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework. AISTATS (2023)
Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi
Robust Offline Policy Evaluation and Optimization with Heavy-Tailed Rewards. CoRR (2023)
Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song
Multiplier Bootstrap-based Exploration. ICML (2023)
Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. KDD (2023)
Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. CoRR (2023)
Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song
Multiplier Bootstrap-based Exploration. CoRR (2023)
Yu Liu, Runzhe Wan, James McQueen, Doug Hains, Jinxiang Gu, Rui Song
Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches. CoRR (2023)
Xiaohong Chen, Zhengling Qi, Runzhe Wan
Singularity-aware Reinforcement Learning. CoRR (2023)
Haoyu Wei, Runzhe Wan, Lei Shi, Rui Song
Zero-Inflated Bandits. CoRR (2023)
Chengchun Shi, Runzhe Wan, Ge Song, Shikai Luo, Rui Song, Hongtu Zhu
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets. CoRR (2022)
Runzhe Wan, Lin Ge, Rui Song
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework. CoRR (2022)
Runzhe Wan, Yingying Li, Wenbin Lu, Rui Song
Mining the Factor Zoo: Estimation of Latent Factor Models with Sufficient Proxies. CoRR (2022)
Runzhe Wan, Branislav Kveton, Rui Song
Safe Exploration for Efficient Policy Evaluation and Comparison. ICML (2022)
Runzhe Wan, Branislav Kveton, Rui Song
Safe Exploration for Efficient Policy Evaluation and Comparison. CoRR (2022)
Ye Shen, Runzhe Wan, Hengrui Cai, Rui Song
Heterogeneous Synthetic Learner for Panel Data. CoRR (2022)
Runzhe Wan, Sheng Zhang, Chengchun Shi, Shikai Luo, Rui Song
Pattern Transfer Learning for Reinforcement Learning in Order Dispatching. CoRR (2021)
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Deeply-Debiased Off-Policy Interval Estimation. CoRR (2021)
Runzhe Wan, Xinyu Zhang, Rui Song
Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control. KDD (2021)
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Deeply-Debiased Off-Policy Interval Estimation. ICML (2021)
Runzhe Wan, Lin Ge, Rui Song
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models. CoRR (2021)
Runzhe Wan, Lin Ge, Rui Song
Metadata-based Multi-Task Bandits with Bayesian Hierarchical Models. NeurIPS (2021)
Runzhe Wan, Xinyu Zhang, Rui Song
Multi-Objective Reinforcement Learning for Infectious Disease Control with Application to COVID-19 Spread. CoRR (2020)
Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. CoRR (2020)
Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. ICML (2020)