Separation of Nonergodic Uniform Convergence Rates for Regularized Learning in Games
Convergence of Optimistic Learning in Games and the Role of Forgetfulness Online learning algorithms solve games by repeatedly updating players’ strategies. A natural hope is that the latest strategy improves at a predictable rate. This paper shows that this intuition can fail for optimistic follow-the-regularized-lea...