Supplementary projections for the acceleration of Kaczmarz algorithm
type: Item
instance of: scholarly article
title: Supplementary projections for the acceleration of Kaczmarz algorithm
zbMATH Open document ID: 1410.65117
author: I. Pomparău
author: Constantin Popa
published in: Applied Mathematics and Computation
publication date: 2018-06-22T00:00:00Z
Mathematics Subject Classification ID: 65F20
Mathematics Subject Classification ID: 65F10
zbMATH DE Number: 6893605
zbMATH Keywords: Kaczmarz algorithm
zbMATH Keywords: direct projection methods
zbMATH Keywords: least squares problems
zbMATH Keywords: accelerating convergence of iterative method
zbMATH Keywords: conserving the sparsity pattern
describes a project that uses: symrcm
MaRDI profile type: Publication
full work available at URL: j.amc.2014.01.098
OpenAlex ID: W1972417355
cites work: Projection method for solving a singular system of linear equations and its applications
cites work: Q4109207
cites work: Accelerated projection methods for computing pseudoinverse solutions of systems of linear equations
cites work: Row-Action Methods for Huge and Sparse Systems and Their Applications
cites work: Iterative algorithms for large partitioned linear systems, with applications to image reconstruction
cites work: Strong underrelaxation in Kaczmarz's method for inconsistent systems
cites work: Parallel and sequential Kaczmarz methods for solving underdetermined nonlinear equations
cites work: Extensions of block-projections methods with relaxation parameters to inconsistent and rank-deficient least-squares problems
cites work: A randomized Kaczmarz algorithm with exponential convergence
cites work: Least-squares solution of overdetermined inconsistent linear systems using kaczmarz's relaxation
cites work: A stationary iterative pseudoinverse algorithm
cites work: On Kaczmarz's projection iteration as a direct solver for linear least squares problems
cites work: Sparse Matrices in MATLAB: Design and Implementation
cites work: Q4718793
cites work: Fundamentals of Computerized Tomography
cites work: Data Clustering: Theory, Algorithms, and Applications
DOI: 10.1016/J.AMC.2014.01.098
description: scientific article; zbMATH DE number 6893605