Hybrid Jacobian and Gauss--Seidel Proximal Block Coordinate Update Methods for Linearly Constrained Convex Programming
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Publication:4609466
DOI10.1137/16M1084705zbMath1384.90072arXiv1608.03928OpenAlexW2963546783MaRDI QIDQ4609466
Publication date: 3 April 2018
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1608.03928
alternating direction method of multipliers (ADMM)Gauss-Seidel ruleblock coordinate update (BCU)Jacobian rule
Analysis of algorithms (68W40) Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Computational methods for problems pertaining to operations research and mathematical programming (90-08)
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Synchronous parallel block coordinate descent method for nonsmooth convex function minimization ⋮ Unnamed Item ⋮ Asynchronous parallel primal-dual block coordinate update methods for affinely constrained convex programs ⋮ Accelerated primal-dual proximal block coordinate updating methods for constrained convex optimization ⋮ CoordinateWise Descent Methods for Leading Eigenvalue Problem ⋮ Randomized primal-dual proximal block coordinate updates
Uses Software
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