Two-timescale Extragradient for Finding Local Minimax Points

Chae, Jiseok, Kim, Kyuwon, Kim, Donghwan

arXiv.org Artificial Intelligence 

Minimax problems are notoriously challenging to optimize. However, we demonstrate that the two-timescale extragradient can be a viable solution. By utilizing dynamical systems theory, we show that it converges to points that satisfy the second-order necessary condition of local minimax points, under a mild condition. This work surpasses all previous results as we eliminate a crucial assumption that the Hessian, with respect to the maximization variable, is nondegenerate.

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