Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback

Ofir Schlisselberg, Tal Lancewicki, Peter Auer +1

We study the multi-armed bandit problem with adversarially chosen delays in the Best-of-Both-Worlds (BoBW) framework, which aims to achieve near-optimal performance in both stochas…