Generalized ADMM with optimal indefinite proximal term for linearly constrained convex optimization
From MaRDI portal
Publication:781096
DOI10.3934/jimo.2018181zbMath1449.90290OpenAlexW2907514291MaRDI QIDQ781096
Zhongming Wu, Fan Jiang, Xing-Ju Cai
Publication date: 16 July 2020
Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/jimo.2018181
convex programmingconvergence rateoptimal rangegeneralized alternating direction method of multipliersindefinite proximal term
Numerical mathematical programming methods (65K05) Convex programming (90C25) Decomposition methods (49M27)
Related Items
Linearized symmetric multi-block ADMM with indefinite proximal regularization and optimal proximal parameter ⋮ The developments of proximal point algorithms ⋮ Majorized iPADMM for Nonseparable Convex Minimization Models with Quadratic Coupling Terms ⋮ An indefinite proximal subgradient-based algorithm for nonsmooth composite optimization ⋮ A Zeroth-Order Proximal Stochastic Gradient Method for Weakly Convex Stochastic Optimization ⋮ Inexact generalized ADMM with relative error criteria for linearly constrained convex optimization problems ⋮ A multi-parameter parallel ADMM for multi-block linearly constrained separable convex optimization ⋮ An indefinite proximal Peaceman-Rachford splitting method with substitution procedure for convex programming ⋮ An inexact symmetric ADMM algorithm with indefinite proximal term for sparse signal recovery and image restoration problems ⋮ The indefinite proximal point algorithms for maximal monotone operators ⋮ An inexact ADMM with proximal-indefinite term and larger stepsize
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nonlinear total variation based noise removal algorithms
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- PPA-like contraction methods for convex optimization: a framework using variational inequality approach
- A proximal alternating linearization method for minimizing the sum of two convex functions
- Removing multiplicative noise by Douglas-Rachford splitting methods
- On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- Some convergence properties of a method of multipliers for linearly constrained monotone variational inequalities
- A new method for a class of linear variational inequalities
- Linearized alternating direction method of multipliers for sparse group and fused Lasso models
- Convergence analysis of the generalized alternating direction method of multipliers with logarithmic-quadratic proximal regularization
- Alternating direction method for covariance selection models
- On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
- Generalized alternating direction method of multipliers: new theoretical insights and applications
- Exact matrix completion via convex optimization
- A Majorized ADMM with Indefinite Proximal Terms for Linearly Constrained Convex Composite Optimization
- Proximal Splitting Methods in Signal Processing
- A Strictly Contractive Peaceman--Rachford Splitting Method for Convex Programming
- Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
- A Proximal Strictly Contractive Peaceman--Rachford Splitting Method for Convex Programming with Applications to Imaging
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- Atomic Decomposition by Basis Pursuit
- Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization
- On Alternating Direction Methods of Multipliers: A Historical Perspective
- Restoration of Poissonian Images Using Alternating Direction Optimization
- Signal Recovery by Proximal Forward-Backward Splitting
