Sparse sampling Kaczmarz–Motzkin method with linear convergence

DOI10.1002/mma.7990zbMath1527.65024arXiv2101.04807OpenAlexW3119500395MaRDI QIDQ6139724

Hong-Xia Wang, Hui Zhang, Ziyang Yuan

Publication date: 19 December 2023

Published in: Mathematical Methods in the Applied Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2101.04807

zbMATH Keywords

Bregman projectionsampling Kaczmarz-Motzkinsparse Kaczmarz method

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20)

Related Items (1)

Adaptively sketched Bregman projection methods for linear systems

Cites Work

• Acceleration of randomized Kaczmarz method via the Johnson-Lindenstrauss lemma
• Block Kaczmarz method with inequalities
• A randomized Kaczmarz algorithm with exponential convergence
• Linear convergence of the randomized sparse Kaczmarz method
• A dual algorithm for a class of augmented convex signal recovery models
• Paved with good intentions: analysis of a randomized block Kaczmarz method
• Augmented $\ell_1$ and Nuclear-Norm Models with a Globally Linearly Convergent Algorithm
• The Linearized Bregman Method via Split Feasibility Problems: Analysis and Generalizations
• The university of Florida sparse matrix collection
• Randomized Methods for Linear Constraints: Convergence Rates and Conditioning

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