First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems

24 Oct 2018Mingrui LiuHassan RafiqueQihang LinTianbao Yang

In this paper, we consider first-order convergence theory and algorithms for solving a class of non-convex non-concave min-max saddle-point problems, whose objective function is weakly convex in the variables of minimization and weakly concave in the variables of maximization. It has many important applications in machine learning including training Generative Adversarial Nets (GANs)... (read more)

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