A parameterized Douglas-Rachford Splitting algorithm for nonconvex optimization

Autor:	Bian, Fengmiao, Zhang, Xiaoqun
Rok vydání:	2019
Předmět:	Mathematics - Optimization and Control
Druh dokumentu:	Working Paper
Popis:	In this paper, we study a parameterized Douglas-Rachford splitting method for a class of nonconvex optimization problem. A new merit function is constructed to establish the convergence of the whole sequence generated by the parameterized Douglas-Rachford splitting method. We then apply the parameterized Douglas-Rachford splitting method to three important classes of nonconvex optimization problems arising in data science: sparsity constrained least squares problem, feasibility problem and low rank matrix completion. Numerical results validate the effectiveness of the parameterized Douglas-Rachford splitting method compared with some other classical methods. Comment: 26 pages. submitted. Some changes have made
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1910.05544 Zobrazit plný text záznamu View this record from Arxiv