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max

Neural Information Processing Systems

The problem(1) with µy > 0 is called a weakly convex-strongly concave(WCSC) saddle-point problem, whereas forµy =0,itiscalledaweakly convex-merely concave(WCMC) saddle-point problem.


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