An algorithmic framework of generalized primal-dual hybrid gradient methods for saddle point problems
type: Item
instance of: scholarly article
title: An algorithmic framework of generalized primal-dual hybrid gradient methods for saddle point problems
zbMATH Open document ID: 1387.90186
author: Feng Ma
author: Bingsheng He
author: Xiaoming Yuan
published in: Journal of Mathematical Imaging and Vision
publication date: 2018-02-28T00:00:00Z
Mathematics Subject Classification ID: 90C25
Mathematics Subject Classification ID: 68U10
Mathematics Subject Classification ID: 94A08
zbMATH DE Number: 6845299
zbMATH Keywords: convex programming
zbMATH Keywords: saddle point problem
zbMATH Keywords: image restoration
zbMATH Keywords: variational models
zbMATH Keywords: primal-dual hybrid gradient method
zbMATH Keywords: convergence rate
zbMATH Keywords: variational inequalities
MaRDI profile type: Publication
full work available at URL: s10851-017-0709-5
OpenAlex ID: W2589182068
cites work: Q3266142
cites work: Q4077092
cites work: On the convergence of primal-dual hybrid gradient algorithms for total variation image restoration
cites work: An algorithm for total variation minimization and applications
cites work: A first-order primal-dual algorithm for convex problems with applications to imaging
cites work: On the ergodic convergence rates of a first-order primal-dual algorithm
cites work: A remark on accelerated block coordinate descent for computing the proximity operators of a sum of convex functions
cites work: A primal-dual splitting method for convex optimization involving Lipschitzian, proximable and linear composite terms
cites work: On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
cites work: A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
cites work: Finite-Dimensional Variational Inequalities and Complementarity Problems
cites work: Q4144736
cites work: Modified Lagrangians in convex programming and their generalizations
cites work: On the Convergence of Primal-Dual Hybrid Gradient Algorithm
cites work: Convergence analysis of primal-dual algorithms for a saddle-point problem: from contraction perspective
cites work: On the \(O(1/n)\) convergence rate of the Douglas-Rachford alternating direction method
cites work: On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
cites work: Q4110807
cites work: Splitting Algorithms for the Sum of Two Nonlinear Operators
cites work: Q5618030
cites work: Q3905081
cites work: Nonlinear total variation based noise removal algorithms
cites work: Efficient Schemes for Total Variation Minimization Under Constraints in Image Processing
cites work: A unified primal-dual algorithm framework based on Bregman iteration
DOI: 10.1007/S10851-017-0709-5
description: scientific article; zbMATH DE number 6845299