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Zhang, J.H. and Guo, J.H. (2020) On Relaxed Greedy Randomized Coordinate Descent Methods for Solving Large Linear Least-Squares Problems. Applied Numerical Mathematics, 157, 372-384.
https://doi.org/10.1016/j.apnum.2020.06.014

has been cited by the following article:

• TITLE: A Count Sketch Maximal Weighted Residual Kaczmarz Method with Oblique Projection for Highly Overdetermined Linear Systems

  AUTHORS: Peng Zhang, Longyan Li, Pingping Zhang

  KEYWORDS: Count Sketch, Oblique Projection, Kaczmarz Method, Linear System

  JOURNAL NAME: Advances in Pure Mathematics, Vol.12 No.4, April 11, 2022

  ABSTRACT: Motivated by the count sketch maximal weighted residual Kaczmarz (CS-MWRK) method presented by Zhang and Li (Appl. Math. Comput., 410, 126486), we combine the count sketch tech with the maximal weighted residual Kaczmarz Method with Oblique Projection (MWRKO) constructed by Wang, Li, Bao and Liu (arXiv: 2106.13606) to develop a new method for solving highly overdetermined linear systems. The convergence rate of the new method is analyzed. Numerical results demonstrate that our method performs better in computing time compared with the CS-MWRK and MWRKO methods.