@article{Dai2026, 
author = {Lifang Dai and Maolin Liang and Qun Li and Ruijuan Zhao and Yong-hong Shen},
title = {The k-means clustering-based CD method for solving large-scale matrix equation    A  X  =  B},
year = {2026},
journal = {AIMS Mathematics},
volume = {11},
number = {4},
pages = {8859-8878},
keywords = {matrix equation, least-squares, k-means clustering, coordinate descent method},
url = {https://www.sciopen.com/article/10.3934/math.2026365},
doi = {10.3934/math.2026365},
abstract = {In this paper, the coordinate descent (CD) method  integrated with k-means clustering is proposed to address the least-squares problem  of the large-scale matrix equation    A  X  =  B, where the coefficient matrix    A is assumed to be of full column rank. Rigorous theoretical analysis shows that the iteration sequence generated by this method converges to the unique least-norm least-squares solution of the problem. The performed numerical results demonstrate that the method developed here is feasible and efficient.}
}