3 papers
cs.LG2026
Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
Xiangkun Wu, Qianglin Wen, Yingying Zhang +3
A/B testing has become a gold standard for modern technological companies to conduct policy evaluation. Yet, its application to time series experiments, where policies are sequenti…
stat.ML2025
Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation
Feichen Gan, Youcun Lu, Yingying Zhang +1
Reliable uncertainty quantification is crucial for reinforcement learning (RL) in high-stakes settings. We propose a unified conformal prediction framework for infinite-horizon pol…
stat.ML2022
Conformal Off-policy Prediction
Yingying Zhang, Chengchun Shi, Shikai Luo
Off-policy evaluation is critical in a number of applications where new policies need to be evaluated offline before online deployment. Most existing methods focus on the expected…