Splitting augmented Lagrangian-type algorithms with partial quadratic approximation to solve sparse signal recovery problems
From MaRDI portal
Publication:6572453
DOI10.1016/j.cam.2024.115972MaRDI QIDQ6572453
Jin-Bao Jian, Qiongxuan Huang, Jianghua Yin, Wei Zhang
Publication date: 15 July 2024
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Alternating direction method of multipliers for penalized zero-variance discriminant analysis
- A modified alternating direction method for convex quadratically constrained quadratic semidefinite programs
- Alternating direction augmented Lagrangian methods for semidefinite programming
- Lectures on convex optimization
- Monotone splitting sequential quadratic optimization algorithm with applications in electric power systems
- Convergence study of indefinite proximal ADMM with a relaxation factor
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- A new piecewise quadratic approximation approach for \(L_0\) norm minimization problem
- Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis
- Global convergence of ADMM in nonconvex nonsmooth optimization
- An incremental aggregated proximal ADMM for linearly constrained nonconvex optimization with application to sparse logistic regression problems
- Self-adaptive projection-based prediction-correction method for constrained variational inequalities
- A hybrid Bregman alternating direction method of multipliers for the linearly constrained difference-of-convex problems
- Multiplier and gradient methods
- The multiplier method of Hestenes and Powell applied to convex programming
- Hankel Matrix Rank Minimization with Applications to System Identification and Realization
- Constrained Total Variation Deblurring Models and Fast Algorithms Based on Alternating Direction Method of Multipliers
- Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems
- An augmented Lagrangian based parallel splitting method for separable convex minimization with applications to image processing
- A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds
- On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
- Global Convergence of Splitting Methods for Nonconvex Composite Optimization
- Splitting Algorithms for the Sum of Two Nonlinear Operators
- A Symmetric Alternating Direction Method of Multipliers for Separable Nonconvex Minimization Problems
- Convergence rate bounds for a proximal ADMM with over-relaxation stepsize parameter for solving nonconvex linearly constrained problems
- Convergence of alternating direction method for minimizing sum of two nonconvex functions with linear constraints
- A Filter Method with Unified Step Computation for Nonlinear Optimization
- An inertial proximal alternating direction method of multipliers for nonconvex optimization
- The Proximal Alternating Direction Method of Multipliers in the Nonconvex Setting: Convergence Analysis and Rates
- Douglas--Rachford Splitting and ADMM for Nonconvex Optimization: Tight Convergence Results
- A Proximal Minimization Algorithm for Structured Nonconvex and Nonsmooth Problems
- Alternating Direction Method of Multipliers for a Class of Nonconvex and Nonsmooth Problems with Applications to Background/Foreground Extraction
- A nonconvex ADMM for a class of sparse inverse semidefinite quadratic programming problems
- Navigating in a Graph by Aid of Its Spanning Tree Metric
This page was built for publication: Splitting augmented Lagrangian-type algorithms with partial quadratic approximation to solve sparse signal recovery problems