Accelerated Bregman method for linearly constrained \(\ell _1-\ell _2\) minimization

DOI10.1007/s10915-013-9686-zzbMath1276.65033OpenAlexW2097845889MaRDI QIDQ368088

Myeongmin Kang, Sangwoon Yun, Hyenkyun Woo, Myungjoo Kang

Publication date: 18 September 2013

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-013-9686-z

zbMATH Keywords

algorithmglobal convergencenumerical examplesaugmented Lagrangian methodimage restorationcompressive sensing\(\ell _1-\ell _2\) minimizationaccelerated Bregman methodBregman iterationlinearized Bregman method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (16)

Reducing the Complexity of Two Classes of Optimization Problems by Inexact Accelerated Proximal Gradient Method ⋮ Solving the TSP by the AALHNN algorithm ⋮ Fast convergence of dynamical ADMM via time scaling of damped inertial dynamics ⋮ Inertial accelerated primal-dual methods for linear equality constrained convex optimization problems ⋮ A Dynamical Splitting Method for Minimizing the Sum of Three Convex Functions ⋮ The modified accelerated Bregman method for regularized basis pursuit problem ⋮ An accelerated augmented Lagrangian method for linearly constrained convex programming with the rate of convergence \(O\left({1/{k^2}} \right)\) ⋮ A novel method for a class of structured low-rank minimizations with equality constraint ⋮ An accelerated proximal augmented Lagrangian method and its application in compressive sensing ⋮ Inexact accelerated augmented Lagrangian methods ⋮ Stability of the elastic net estimator ⋮ Iteration complexity of inexact augmented Lagrangian methods for constrained convex programming ⋮ Accelerated method for optimization over density matrices in quantum state estimation ⋮ Accelerated First-Order Primal-Dual Proximal Methods for Linearly Constrained Composite Convex Programming ⋮ Fast primal-dual algorithm via dynamical system for a linearly constrained convex optimization problem ⋮ A primal-dual flow for affine constrained convex optimization

Uses Software

• L-BFGS
• PDCO
• SPGL1
• L1-MAGIC

Cites Work

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