Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity
In the standard data analysis framework, data is collected (once for all), and then data analysis is carried out. However, with the advancement of digital technology, …
Dynamic Selection in Algorithmic Decision-making
This paper identifies and addresses dynamic selection problems in online learning algorithms with endogenous data. In a contextual multi-armed bandit model, a novel bias …