- Iteration complexity on the Generalized Peaceman-Rachford splitting method for separable convex programming Zhang Xue-Qing (zxqcqspb163.com) Peng Jian-Wen (jwpeng168hotmail.com) Abstract: Recently, a generalized version of Peaceman-Rachford splitting method (GPRSM) for solving a convex minmization model with a general separable structure has been proposed by \textbf{Sun} et al and its global convergence has been proved. In this paper, we further study theoretical aspects of the generalized Peaceman-Rachford splitting method. We first establish the worst-case $\mathcal{O}(1/t)$ convergence rate for the proposed GPRSM in both the ergodic and a nonergodic senses, then we give some numerical results to demonstrate the convergence rate of the algorithm. Keywords: Convex minimization problem; Generalized Peaceman-Rachford splitting method; Iteration complexity; LASSO problem; Matrix optimization. Category 1: Convex and Nonsmooth Optimization (Convex Optimization ) Citation: July 8, 2017 Download: [PDF]Entry Submitted: 07/07/2017Entry Accepted: 07/08/2017Entry Last Modified: 07/07/2017Modify/Update this entry Visitors Authors More about us Links Subscribe, Unsubscribe Digest Archive Search, Browse the Repository Submit Update Policies Coordinator's Board Classification Scheme Credits Give us feedback Optimization Journals, Sites, Societies Optimization Online is supported by the Mathematical Optmization Society.