ImprovedAlgorithmsforConvex-Concave MinimaxOptimization

–Neural Information Processing Systems 

This paper studies minimax optimization problemsminxmaxyf(x,y), where f(x,y) is mx-strongly convex with respect tox, my-strongly concave with respect to y and (Lx,Lxy,Ly)-smooth. Zhang et al. [42] provided the following lower bound of the gradient complexity for any first-order method: Ω q

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