Adrienne M Propp

Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective

Model selection in supervised learning provides costless guarantees as if the model that best balances bias and variance was known a priori. We study the feasibility of similar guarantees for cumulative regret minimization in the stochastic contextual bandit setting. Recent work [Marinov and Zimmert…