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» Document clustering using nonnegative matrix factorization
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ICASSP
2010
IEEE
13 years 8 months ago
Multiplicative update rules for nonnegative matrix factorization with co-occurrence constraints
Nonnegative matrix factorization (NMF) is a widely-used tool for obtaining low-rank approximations of nonnegative data such as digital images, audio signals, textual data, financ...
Steven K. Tjoa, K. J. Ray Liu
BMCBI
2006
170views more  BMCBI 2006»
13 years 8 months ago
Biclustering of gene expression data by non-smooth non-negative matrix factorization
Background: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of gene...
Pedro Carmona-Saez, Roberto D. Pascual-Marqui, Fra...
ICCV
2009
IEEE
15 years 1 months ago
Non-Negative Matrix Factorization of Partial Track Data for Motion Segmentation
This paper addresses the problem of segmenting lowlevel partial feature point tracks belonging to multiple motions. We show that the local velocity vectors at each instant of th...
Anil M. Cheriyadat and Richard J. Radke
ICDM
2008
IEEE
115views Data Mining» more  ICDM 2008»
14 years 3 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
TKDE
2010
224views more  TKDE 2010»
13 years 3 months ago
Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
Yanhua Chen, Lijun Wang, Ming Dong