On the Polyak momentum variants of the greedy deterministic single and multiple row‐action methods

Author:

Wu Nian‐Ci1ORCID,Zuo Qian23,Wang Yatian4

Affiliation:

1. School of Mathematics and Statistics South‐Central Minzu University Wuhan China

2. Center on Frontiers of Computing Studies Peking University Beijing China

3. School of Computer Science Peking University Beijing China

4. School of Mathematics and Statistics Wuhan University Wuhan China

Abstract

AbstractFor solving a consistent system of linear equations, the classical row‐action method, such as Kaczmarz method, is a simple while really effective iteration solver. Based on the greedy index selection strategy and Polyak's heavy‐ball momentum acceleration technique, we propose two deterministic row‐action methods and establish the corresponding convergence theory. We show that our algorithm can linearly converge to a least‐squares solution with minimum Euclidean norm. Several numerical studies have been presented to corroborate our theoretical findings. Real‐world applications, such as data fitting in computer‐aided geometry design, are also presented for illustrative purposes.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Reference44 articles.

1. Angenäherte auflösung von systemen linearer gleichungen;Kaczmarz S;Bull Int Acad Polon Sci A,1937

2. Row-Action Methods for Huge and Sparse Systems and Their Applications

3. Alternating Projection Methods

4. A Randomized Kaczmarz Algorithm with Exponential Convergence

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