Martingale CLTs and Adaptive Linear Regression
Speaker: James Leiner
Abstract: When data is collected in an adaptive manner, even simple methods like ordinary least squares can exhibit non-normal asymptotic behavior. We consider settings with adaptively collected data, such as multi-armed bandit problems, and demonstrate how martingale CLTs can be used to provide accurate inference in linear regression problems. The talk will be based on the following papers: https://projecteuclid.org/journals/annals-of-statistics/volume-10/issue-1/Least-Squares-Estimates-in-Stochastic-Regression-Models-with-Applications-to/10.1214/aos/1176345697.full, https://arxiv.org/abs/1712.06695, https://arxiv.org/abs/2002.03217, https://arxiv.org/pdf/2107.02266