3 papers
stat.ML2026
Sparse Additive Off-Policy Evaluation for Reinforcement Learning with Potentially Limited Number of Trajectories
Tuoyi Zhao, Chengchun Shi, Zhengling Qi +1
We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle large state spaces and support tr…
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…
cs.LG2022
Blessing from Human-AI Interaction: Super Reinforcement Learning in Confounded Environments
Jiayi Wang, Zhengling Qi, Chengchun Shi
As AI becomes more prevalent throughout society, effective methods of integrating humans and AI systems that leverage their respective strengths and mitigate risk have become an im…