Department of Mathematics
A splitting method for separable convex programming
© 2014 The Authors. We propose a splitting method for solving a separable convex minimization problem with linear constraints, where the objective function is expressed as the sum of m individual functions without coupled variables. Treating the functions in the objective separately, the new method belongs to the category of operator splitting methods. We show the global convergence and estimate a worst-case convergence rate for the new method, and then illustrate its numerical efficiency by some applications.
convex programming, image processing, operator splitting methods, separable structure
Source Publication Title
IMA Journal of Numerical Analysis
Oxford University Press
Link to Publisher's Edition
He, Bingsheng, Min Tao, and Xiaoming Yuan. "A splitting method for separable convex programming." IMA Journal of Numerical Analysis 35.1 (2015): 394-426.