Stochastic Methods Based on VU-Decomposition Methods for Stochastic Convex Minimax Problems

الملخص EN

This paper applies sample average approximation (SAA) method based on VU-space decomposition theory to solve stochastic convex minimax problems.

Under some moderate conditions, the SAA solution converges to its true counterpart with probability approaching one and convergence is exponentially fast with the increase of sample size.

Based on the VU-theory, a superlinear convergent VU-algorithm frame is designed to solve the SAA problem.