1. A proximal alternating linearization method for nonconvex optimization problems.
- Author
-
Li, Dan, Pang, Li-Ping, and Chen, Shuang
- Subjects
- *
NONSMOOTH optimization , *NONCONVEX programming , *APPROXIMATION theory , *ITERATIVE methods (Mathematics) , *STOCHASTIC convergence , *NUMERICAL analysis - Abstract
In this paper, we focus on the problems of minimizing the sum of two nonsmooth functions which are possibly nonconvex. These problems arise in many applications of practical interests. We present a proximal alternating linearization algorithm which alternately generates two approximate proximal points of the original objective function. It is proved that the accumulation points of iterations converge to a stationary point of the problem. Numerical experiments validate the theoretical convergence analysis and verify the implementation of the proposed algorithm. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
- Full Text
- View/download PDF