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ISNN
2007
Springer
14 years 2 months ago
Regularized Alternating Least Squares Algorithms for Non-negative Matrix/Tensor Factorization
Nonnegative Matrix and Tensor Factorization (NMF/NTF) and Sparse Component Analysis (SCA) have already found many potential applications, especially in multi-way Blind Source Separ...
Andrzej Cichocki, Rafal Zdunek
ICDM
2008
IEEE
115views Data Mining» more  ICDM 2008»
14 years 2 months ago
Toward Faster Nonnegative Matrix Factorization: A New Algorithm and Comparisons
Nonnegative Matrix Factorization (NMF) is a dimension reduction method that has been widely used for various tasks including text mining, pattern analysis, clustering, and cancer ...
Jingu Kim, Haesun Park
CVPR
2009
IEEE
13 years 11 months ago
Nonnegative Matrix Factorization with Earth Mover's Distance metric
Nonnegative Matrix Factorization (NMF) approximates a given data matrix as a product of two low rank nonnegative matrices, usually by minimizing the L2 or the KL distance between ...
Roman Sandler, Michael Lindenbaum
ICCV
2005
IEEE
14 years 9 months ago
Passive Photometric Stereo from Motion
We introduce an iterative algorithm for shape reconstruction from multiple images of a moving (Lambertian) object illuminated by distant (and possibly time varying) lighting. Star...
Jongwoo Lim, Jeffrey Ho, Ming-Hsuan Yang, David J....
BMCBI
2010
155views more  BMCBI 2010»
13 years 8 months ago
A flexible R package for nonnegative matrix factorization
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Renaud Gaujoux, Cathal Seoighe