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ICA
2004
Springer
11 years 6 months ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela
JMLR
2002
73views more  JMLR 2002»
11 years 1 months ago
Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components
We apply a variational method to automatically determine the number of mixtures of independent components in high-dimensional datasets, in which the sources may be nonsymmetricall...
Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski
DSP
2007
11 years 1 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
BMCV
2000
Springer
11 years 5 months ago
The Spectral Independent Components of Natural Scenes
Abstract. We apply independent component analysis (ICA) for learning an eļ¬ƒcient color image representation of natural scenes. In the spectra of single pixels, the algorithm was a...
Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski
ICML
2007
IEEE
12 years 2 months ago
Local dependent components
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
Arto Klami, Samuel Kaski
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