3 papers
stat.ML2026
Double Fairness Policy Learning: Integrating Action Fairness and Outcome Fairness in Decision-making
Zeyu Bian, Lan Wang, Chengchun Shi +1
Fairness is a central pillar of trustworthy machine learning, especially in domains where accuracy- or profit-driven optimization is insufficient. While most fairness research focu…
stat.ML2026
Beyond Demand Estimation: Consumer Surplus Evaluation via Cumulative Propensity Weights
Zeyu Bian, Max Biggs, Ruijiang Gao +1
This paper develops a practical framework for using observational data to audit the consumer surplus effects of AI-driven decisions, specifically in targeted pricing and algorithmi…
cs.LG2024
Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning
Shuguang Yu, Shuxing Fang, Ruixin Peng +3
This paper studies off-policy evaluation (OPE) in the presence of unmeasured confounders. Inspired by the two-way fixed effects regression model widely used in the panel data liter…