Skip to main content
Open Access Publications from the University of California

Department of Statistics, UCLA

Department of Statistics Papers bannerUCLA

A Decomposition Method for Weighted Least Squares Low-rank Approximation of Symmetric Matrices


We discuss an alternating least squares algorithm that uses both decomposition and block relaxation to find the optimal positive semidefinite approxation of given rank p to a known symmetric matrix of order n. Each iteration of the algorithm involves minimizing n quartics and solving n secular equations of order p.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View