COLT 2020Poster
Open Problem: Model Selection for Contextual Bandits
作者: Dylan J Foster, Akshay Krishnamurthy, Haipeng Luo
摘要
In statistical learning, algorithms for model selection allow the learner to adapt to the complexity of the best hypothesis class in a sequence. We ask whether similar guarantees are possible for contextual bandit learning.