Rachel Q. Zhang

A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds

Linear contextual bandits and their variants are usually solved using algorithms guided by parameter estimation. Cauchy-Schwartz inequality established that estimation errors dominate algorithm regrets, and thus, accurate estimators suffice to guarantee algorithms with low regrets. In this paper, we…