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BMCBI
2006
119views more  BMCBI 2006»
13 years 9 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
MOC
2000
65views more  MOC 2000»
13 years 9 months ago
Almost periodic factorization of certain block triangular matrix functions
Let G(x) = eixIm 0 c-1e-ix + c0 + c1eix e-ixIm , where cj Cm
Ilya M. Spitkovsky, Darryl Yong
ICPR
2010
IEEE
14 years 4 months ago
Bayesian Inference for Nonnegative Matrix Factor Deconvolution Models
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...
Serap Kirbiz, Ali Taylan Cemgil, Bilge Gunsel
ICASSP
2008
IEEE
14 years 4 months ago
Fast speaker adaptation using non-negative matrix factorization
This paper describes a new method for fast speaker adaptation in large vocabulary recognition systems. As in most HMM-based recognizers, the observation densities are modeled as a...
Jacques Duchateau, Tobias Leroy, Kris Demuynck, Hu...
ICDM
2008
IEEE
115views Data Mining» more  ICDM 2008»
14 years 4 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