5 papers
Asymptotic Theory and Sequential Testing for Adaptive Bandits
Li Yang, Xiaodong Yan, Dandan Jiang
Multi-armed bandit (MAB) processes constitute a foundational subclass of reinforcement learning problems and represent a central topic in statistical decision theory. Yet, conducti…
Mixed Effects Mixture of Experts: Modeling Double Heterogeneous Trajectories
Xinkai Yue, Xiaodong Yan, Haohui Han +1
Linear mixed-effects model (LMM) is a cornerstone of longitudinal data analysis, but is limited to adeptly make heterogeneous analyses predictable under both group-specific fixed e…
Optimization via Strategic Law of Large Numbers
Xiaohong Chen, Zengjing Chen, Wayne Yuan Gao +2
This paper proposes a unified framework for the global optimization of a continuous function in a bounded rectangular domain. Specifically, we show that: (1) under the optimal stra…
A Two-armed Bandit Framework for A/B Testing
Jinjuan Wang, Qianglin Wen, Yu Zhang +2
A/B testing is widely used in modern technology companies for policy evaluation and product deployment, with the goal of comparing the outcomes under a newly-developed policy again…
Strategic A/B testing via Maximum Probability-driven Two-armed Bandit
Yu Zhang, Shanshan Zhao, Bokui Wan +2
Detecting a minor average treatment effect is a major challenge in large-scale applications, where even minimal improvements can have a significant economic impact. Traditional met…