@Article{EAJAM-12-2,
author = {Jia-Qi, Chen and Zheng-Da, Huang},
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 = {<p style="text-align: justify;">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.</p>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.160721.160122},
url = {https://global-sci.com/article/82473/a-fast-block-coordinate-descent-method-for-solving-linear-least-squares-problems}
}