A very fast algorithm for matrix factorization

Nikulin, V, Huang, TH, Ng, SK, Rathnayake, SI and McLachlan, GJ (2011) A very fast algorithm for matrix factorization. Statistics and Probability Letters, 81 7: 773-782.


Author Nikulin, V
Huang, TH
Ng, SK
Rathnayake, SI
McLachlan, GJ
Title A very fast algorithm for matrix factorization
Journal name Statistics and Probability Letters  (ERA 2012 Listed)    (ERA 2010 Rank B)   Check publisher's open access policy
Publication date 2011-07
Sub-type Article
DOI 10.1016/j.spl.2011.02.001
Volume number 81
Issue number 7
ISSN 0167-7152
Start page 773
End page 782
Total pages 10
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Collection year 2012
Language eng
Abstract We present a very fast algorithm for general matrix factorization of a data matrix for use in the statistical analysis of high-dimensional data via latent factors. Such data are prevalent across many application areas and generate an ever-increasing demand for methods of dimension reduction in order to undertake the statistical analysis of interest. Our algorithm uses a gradient-based approach which can be used with an arbitrary loss function provided the latter is differentiable. The speed and effectiveness of our algorithm for dimension reduction is demonstrated in the context of supervised classification of some real high-dimensional data sets from the bioinformatics literature. © 2011 Elsevier B.V.
Keyword High-dimensional data
Matrix factorization
Microarray gene-expression data
Nonnegative matrix factorization
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Journal issue: Statistics in Biological and Medical Sciences

 
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Created: Wed, 18 May 2011, 16:02:38 EST by Dr Suren Indrajith Rathnayake on behalf of Mathematics