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» Algorithms for Non-negative Matrix Factorization
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SIGIR
2005
ACM
15 years 3 months ago
Relation between PLSA and NMF and implications
Non-negative Matrix Factorization (NMF, [5]) and Probabilistic Latent Semantic Analysis (PLSA, [4]) have been successfully applied to a number of text analysis tasks such as docum...
Éric Gaussier, Cyril Goutte
BMCBI
2006
170views more  BMCBI 2006»
14 years 9 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...
CORR
2004
Springer
152views Education» more  CORR 2004»
14 years 9 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer
85
Voted
CVPR
2001
IEEE
15 years 11 months ago
Learning Representative Local Features for Face Detection
This paper describes a face detection approach via learning local features. The key idea is that local features, being manifested by a collection of pixels in a local region, are ...
Xiangrong Chen, Lie Gu, Stan Z. Li, HongJiang Zhan...
CORR
2008
Springer
113views Education» more  CORR 2008»
14 years 9 months ago
Clustering of scientific citations in Wikipedia
The instances of templates in Wikipedia form an interesting data set of structured information. Here I focus on the cite journal template that is primarily used for citation to art...
Finn Årup Nielsen