TITLE:
Continuous Iteratively Reweighted Least Squares Algorithm for Solving Linear Models by Convex Relaxation
AUTHORS:
Xian Luo, Wanzhou Ye
KEYWORDS:
Linear Models, Continuous Iteratively Reweighted Least Squares, Convex Relaxation, Principal Component Analysis
JOURNAL NAME:
Advances in Pure Mathematics,
Vol.9 No.6,
June
27,
2019
ABSTRACT: In this paper, we present continuous iteratively reweighted
least squares algorithm (CIRLS) for solving
the linear models problem by convex relaxation, and prove the convergence of
this algorithm. Under some conditions, we give an error bound for the
algorithm. In addition, the numerical result shows the efficiency of the
algorithm.