A primal majorized semismooth Newton-CG augmented Lagrangian method for large-scale linearly constrained convex programming
type: Item
instance of: scholarly article
title: A primal majorized semismooth Newton-CG augmented Lagrangian method for large-scale linearly constrained convex programming
zbMATH Open document ID: 1394.90465
author: Peipei Tang
author: Cheng-Jing Wang
published in: Computational Optimization and Applications
publication date: 2018-02-01T00:00:00Z
Mathematics Subject Classification ID: 90C25
Mathematics Subject Classification ID: 90C22
Mathematics Subject Classification ID: 90C53
zbMATH DE Number: 6833518
zbMATH Keywords: majorized semismooth Newton-CG augmented Lagrangian method
zbMATH Keywords: iteration complexity
zbMATH Keywords: quadratic semidefinite programming
describes a project that uses: SDPNAL+
describes a project that uses: QSDPNAL
describes a project that uses: QSDP
MaRDI profile type: Publication
full work available at URL: s10589-017-9930-9
OpenAlex ID: W2739853462
cites work: Convex Analysis
cites work: Variational Analysis
cites work: Q3845569
cites work: Monotone Operators and the Proximal Point Algorithm
cites work: Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
cites work: Iteration-complexity of first-order augmented Lagrangian methods for convex programming
cites work: A SURVEY OF NUMERICAL METHODS FOR NONLINEAR SEMIDEFINITE PROGRAMMING
cites work: An Accelerated Linearized Alternating Direction Method of Multipliers
cites work: A Newton-CG Augmented Lagrangian Method for Semidefinite Programming
cites work: The rate of convergence of the augmented Lagrangian method for nonlinear semidefinite programming
cites work: Complementarity and nondegeneracy in semidefinite programming
cites work: A Quadratically Convergent Newton Method for Computing the Nearest Correlation Matrix
cites work: A majorized ADMM with indefinite proximal terms for linearly constrained convex composite optimization
cites work: An implementable proximal point algorithmic framework for nuclear norm minimization
cites work: An augmented Lagrangian dual approach for the H-weighted nearest correlation matrix problem
cites work: Solving Log-Determinant Optimization Problems by a Newton-CG Primal Proximal Point Algorithm
cites work: SDPNAL+: a majorized semismooth Newton-CG augmented Lagrangian method for semidefinite programming with nonnegative constraints
cites work: First-order methods of smooth convex optimization with inexact oracle
cites work: Computational Complexity of Inexact Gradient Augmented Lagrangian Methods: Application to Constrained MPC
cites work: An efficient inexact symmetric Gauss-Seidel based majorized ADMM for high-dimensional convex composite conic programming
cites work: Hankel matrix rank minimization with applications to system identification and realization
cites work: An inexact primal-dual path following algorithm for convex quadratic SDP
cites work: Q5442492
cites work: On how to solve large-scale log-determinant optimization problems
DOI: 10.1007/S10589-017-9930-9
description: scientific article; zbMATH DE number 6833518