Liu, Y., Jiang, X.L. and Gu, C.Q. (2021) On Maximum Residual Block and Two-Step Gauss-Seidel Algorithms for Linear Least-Squares Problems. Calcolo, 58, Article No. 13.
https://doi.org/10.1007/s10092-021-00404-x

has been cited by the following article:

• TITLE: Greedy Randomized Gauss-Seidel Method with Oblique Direction

  AUTHORS: Weifeng Li, Pingping Zhang

  KEYWORDS: Oblique Direction, Linear Least Squares Problem, Gauss-Seidel Method

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.11 No.4, April 27, 2023

  ABSTRACT: For the linear least squares problem with coefficient matrix columns being highly correlated, we develop a greedy randomized Gauss-Seidel method with oblique direction. Then the corresponding convergence result is deduced. Numerical examples demonstrate that our proposed method is superior to the greedy randomized Gauss-Seidel method and the randomized Gauss-Seidel method with oblique direction.