We study the convergence of optimistic gradient descent ascent in unconstrained bilinear games. For zero-sum games, we prove exponential convergence to a saddle-point for any payoff matrix, and provide the exact ratio of convergence as a function of the step size. Then, we introduce ...
In this section, we focus on analyzing the performance of optimistic gradient descent ascent (OGDA) for solving a general smooth convex-concave saddle point problem. It has been shown that the OGDA method recovers the convergence rate of the proximal point for both strongly convex-strongly concav...
the efficient representation of graphical games as well the expressive power of EFGs. We examine the convergence properties ofOptimistic Gradient Ascent(OGA) in these games. We prove that the time-average behavior of such online learning dynamics exhibitsO(1/T) rate of convergence to the set of...
We study the iteration complexity of the optimistic gradient descent-ascent (OGDA) method and the extragradient (EG) method for finding a saddle point of a convex-concave unconstrained min-max problem. To do so, we first show that both OGDA and EG can be interpreted as approximate variants ...