The proximal alternating minimization algorithm for two-block separable convex optimization problems with linear constraints

DOI10.1007/s10957-018-01454-yOpenAlexW2964189474WikidataQ93144945 ScholiaQ93144945MaRDI QIDQ2315259

Gert Wanka, Radu Ioan Boţ, Ernö Robert Csetnek, Sandy Bitterlich

Publication date: 2 August 2019

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1806.00260

zbMATH Keywords

convex optimizationsubdifferentialLagrangiansaddle pointsFenchel dualityproximal AMA

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Monotone operators and generalizations (47H05)

Related Items

Continuous dynamics related to monotone inclusions and non-smooth optimization problems ⋮ Regularized quasi-monotone method for stochastic optimization ⋮ A Dynamical Approach to Two-Block Separable Convex Optimization Problems with Linear Constraints ⋮ A partially inexact proximal alternating direction method of multipliers and its iteration-complexity analysis

Uses Software

• UNLocBoX

Cites Work

• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• Variable metric quasi-Fejér monotonicity
• A block coordinate variable metric forward-backward algorithm
• Conjugate duality in convex optimization
• A dual algorithm for the solution of nonlinear variational problems via finite element approximation
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Fixing and extending some recent results on the ADMM algorithm
• Convergence analysis for a primal-dual monotone + skew splitting algorithm with applications to total variation minimization
• On the convergence rate improvement of a primal-dual splitting algorithm for solving monotone inclusion problems
• A proximal point analysis of the preconditioned alternating direction method of multipliers
• ADMM for monotone operators: convergence analysis and rates
• Hankel Matrix Rank Minimization with Applications to System Identification and Realization
• Proximal Splitting Methods in Signal Processing
• A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
• Applications of a Splitting Algorithm to Decomposition in Convex Programming and Variational Inequalities
• Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization
• Preconditioned Douglas--Rachford Splitting Methods for Convex-concave Saddle-point Problems
• Convex analysis and monotone operator theory in Hilbert spaces

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