A proximal alternating linearization method for minimizing the sum of two convex functions
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Publication:892779
DOI10.1007/s11425-015-4986-4zbMath1325.90070OpenAlexW1966102749MaRDI QIDQ892779
Zehui Jia, Wenxing Zhang, Xing-Ju Cai
Publication date: 12 November 2015
Published in: Science China. Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11425-015-4986-4
Convex programming (90C25) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Smooth minimization of non-smooth functions
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Fast alternating linearization methods for minimizing the sum of two convex functions
- On the convergence of the proximal algorithm for nonsmooth functions involving analytic features
- Application of the alternating direction method of multipliers to separable convex programming problems
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- A proximal-based deomposition method for compositions method for convex minimization problems
- Introductory lectures on convex optimization. A basic course.
- A new inexact alternating directions method for monotone variational inequalities
- Alternating direction method for covariance selection models
- Further applications of a splitting algorithm to decomposition in variational inequalities and convex programming
- Alternating proximal gradient method for convex minimization
- A customized Douglas-Rachford splitting algorithm for separable convex minimization with linear constraints
- Multiplier and gradient methods
- Exact matrix completion via convex optimization
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- Alternating Direction Method with Gaussian Back Substitution for Separable Convex Programming
- Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
- Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing
- An augmented Lagrangian based parallel splitting method for separable convex minimization with applications to image processing
- Coupling Forward-Backward with Penalty Schemes and Parallel Splitting for Constrained Variational Inequalities
- Deblurring Images
- An EM algorithm for wavelet-based image restoration
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
- Atomic Decomposition by Basis Pursuit
- Proximal Decomposition Via Alternating Linearization
- The Linearized Alternating Direction Method of Multipliers for Dantzig Selector
- On Alternating Direction Methods of Multipliers: A Historical Perspective
