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» Algorithms for Non-negative Matrix Factorization
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SIGIR
2005
ACM
14 years 1 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»
13 years 7 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»
13 years 7 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
CVPR
2001
IEEE
14 years 9 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»
13 years 7 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