arrow
Volume 12, Issue 2
A Fast Block Coordinate Descent Method for Solving Linear Least-Squares Problems

Jia-Qi Chen & Zheng-Da Huang

East Asian J. Appl. Math., 12 (2022), pp. 406-420.

Published online: 2022-02

Export citation
  • Abstract

A fast block coordinate descent method for solving linear least-squares problems is proposed. The method is based on a greedy criterion of the column selection used at each iteration. It is proven that if the coefficient matrix of the corresponding system has full column rank, the method converges to the unique solution of the linear least-squares problem. Numerical experiments show the advantage of this approach over similar methods in terms of CPU time and computational cost, does not matter whether the coefficient matrix is of full column rank or not.

  • AMS Subject Headings

65F10, 65F20, 65K05, 90C25, 15A06

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{EAJAM-12-406, author = {Chen , Jia-Qi and Huang , Zheng-Da}, title = {A Fast Block Coordinate Descent Method for Solving Linear Least-Squares Problems}, journal = {East Asian Journal on Applied Mathematics}, year = {2022}, volume = {12}, number = {2}, pages = {406--420}, abstract = {

A fast block coordinate descent method for solving linear least-squares problems is proposed. The method is based on a greedy criterion of the column selection used at each iteration. It is proven that if the coefficient matrix of the corresponding system has full column rank, the method converges to the unique solution of the linear least-squares problem. Numerical experiments show the advantage of this approach over similar methods in terms of CPU time and computational cost, does not matter whether the coefficient matrix is of full column rank or not.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.160721.160122}, url = {http://global-sci.org/intro/article_detail/eajam/20261.html} }
TY - JOUR T1 - A Fast Block Coordinate Descent Method for Solving Linear Least-Squares Problems AU - Chen , Jia-Qi AU - Huang , Zheng-Da JO - East Asian Journal on Applied Mathematics VL - 2 SP - 406 EP - 420 PY - 2022 DA - 2022/02 SN - 12 DO - http://doi.org/10.4208/eajam.160721.160122 UR - https://global-sci.org/intro/article_detail/eajam/20261.html KW - Linear least-squares problem, Kaczmarz method, coordinate descent method, greedy blocks, convergence. AB -

A fast block coordinate descent method for solving linear least-squares problems is proposed. The method is based on a greedy criterion of the column selection used at each iteration. It is proven that if the coefficient matrix of the corresponding system has full column rank, the method converges to the unique solution of the linear least-squares problem. Numerical experiments show the advantage of this approach over similar methods in terms of CPU time and computational cost, does not matter whether the coefficient matrix is of full column rank or not.

Jia-Qi Chen & Zheng-Da Huang. (2022). A Fast Block Coordinate Descent Method for Solving Linear Least-Squares Problems. East Asian Journal on Applied Mathematics. 12 (2). 406-420. doi:10.4208/eajam.160721.160122
Copy to clipboard
The citation has been copied to your clipboard