Local Low-Rank Matrix Approximation

ICML 2013
Pages: 82 - 90
Published: Jun 16, 2013
Abstract
Matrix approximation is a common tool in recommendation systems, text mining, and computer vision. A prevalent assumption in constructing matrix approximations is that the partially observed matrix is of low-rank. We propose a new matrix approximation model where we assume instead that the matrix is locally of low-rank, leading to a representation of the observed matrix as a weighted sum of low-rank matrices. We analyze the accuracy of the...
Paper Details
Title
Local Low-Rank Matrix Approximation
Published Date
Jun 16, 2013
Journal
Pages
82 - 90
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