The sparse Kaczmarz method with surrogate hyperplane for the regularized basis pursuit problem

Fuente: arXiv
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Hauptverfasser: Wang, Ze, Yin, Jun-Feng, Zhao, Ji-Chen
Format: Preprint
Veröffentlicht: 2024
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author Wang, Ze
Yin, Jun-Feng
Zhao, Ji-Chen
author_facet Wang, Ze
Yin, Jun-Feng
Zhao, Ji-Chen
contents The Sparse Kaczmarz method is a famous and widely used iterative method for solving the regularized basis pursuit problem. A general scheme of the surrogate hyperplane sparse Kaczmarz method is proposed. In particular, a class of residual-based surrogate hyperplane sparse Kaczmarz method is introduced and the implementations are well discussed. Their convergence theories are proved and the linear convergence rates are studied and compared in details. Numerical experiments verify the efficiency of the proposed methods.
format Preprint
id arxiv_https___arxiv_org_abs_2406_15082
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The sparse Kaczmarz method with surrogate hyperplane for the regularized basis pursuit problem
Wang, Ze
Yin, Jun-Feng
Zhao, Ji-Chen
Numerical Analysis
The Sparse Kaczmarz method is a famous and widely used iterative method for solving the regularized basis pursuit problem. A general scheme of the surrogate hyperplane sparse Kaczmarz method is proposed. In particular, a class of residual-based surrogate hyperplane sparse Kaczmarz method is introduced and the implementations are well discussed. Their convergence theories are proved and the linear convergence rates are studied and compared in details. Numerical experiments verify the efficiency of the proposed methods.
title The sparse Kaczmarz method with surrogate hyperplane for the regularized basis pursuit problem
topic Numerical Analysis
url https://arxiv.org/abs/2406.15082