Wing Shing Wong

Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm

This paper studies adversarial bandits with corruptions. In the basic adversarial bandit setting, the reward of arms is predetermined by an adversary who is oblivious to the learner’s policy. In this paper, we consider an extended setting in which an attacker sits in-between the environment and the…