A stochastic preconditioned Douglas-Rachford splitting method for saddle-point problems
- Resource Type
- Working Paper
- Authors
- Dong, Yakun; Bredies, Kristian; Sun, Hongpeng
- Source
- Subject
- Mathematics - Optimization and Control
Mathematics - Numerical Analysis
- Language
In this article, we propose and study a stochastic preconditioned Douglas-Rachford splitting method to solve saddle-point problems which have separable dual variables. We prove the almost sure convergence of the iteration sequences in Hilbert spaces for a class of convexconcave and nonsmooth saddle-point problems. We also provide the sublinear convergence rate for the ergodic sequence with respect to the expectation of the restricted primal-dual gap functions. Numerical experiments show the high efficiency of the proposed stochastic preconditioned Douglas-Rachford splitting methods.