StochasticRecursiveGradientDescentAscentfor StochasticNonconvex-Strongly-ConcaveMinimax Problems

We are interested in finding anO(ε)-stationary point of the functionΦ( ) = maxy Yf( ,y). Thisminimax optimization formulation includes manymachine learning applications such as regularized empirical risk minimization [42, 53], AUC maximization [40, 49], robust optimization [14, 47], adversarial training [16, 17, 41] and reinforcement learning [13, 44].