Convergence Analysis of the Relaxed Proximal Point Algorithm
Recently, a worst-case convergence rate was established for the Douglas-Rachford alternating direction method of multipliers (ADMM) in an ergodic sense. The relaxed proximal point algorithm (PPA) is a generalization of the original PPA which includes the Douglas-Rachford ADMM as a special case. In...
Main Authors: | Min Li, Yanfei You |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2013-01-01
|
Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2013/912846 |
Similar Items
-
About the relaxed cocoercivity and the convergence of the proximal point algorithm
by: Abdellatif Moudafi, et al.
Published: (2013-10-01) -
Super-Relaxed (η)-Proximal Point Algorithms, Relaxed (η)-Proximal Point Algorithms, Linear Convergence Analysis, and Nonlinear Variational Inclusions
by: Ravi P. Agarwal, et al.
Published: (2009-01-01) -
On relaxed and contraction-proximal point algorithms in hilbert spaces
by: Wang Shuyu, et al.
Published: (2011-01-01) -
Relatively Inexact Proximal Point Algorithm and Linear Convergence Analysis
by: Ram U. Verma
Published: (2009-01-01) -
Convergence of a Proximal Point Algorithm for Solving Minimization Problems
by: Abdelouahed Hamdi, et al.
Published: (2012-01-01)