Weighted Low-rank Approximation using Majorization

Abstract

We give a majorization algorithm for weighted low-rank matrix approximation, a.k.a. principal component analysis. There is one non-negative weight for each residual. A quadratic programming method is used to compute optimal rank-one weights for the majorization scheme.