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ICASSP
2011
IEEE
12 years 11 months ago
Variational methods for spectral unmixing of hyperspectral images
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...
KDD
2004
ACM
237views Data Mining» more  KDD 2004»
14 years 8 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
CSDA
2010
194views more  CSDA 2010»
13 years 7 months ago
A clipped latent variable model for spatially correlated ordered categorical data
We propose a model for a point-referenced spatially correlated ordered categorical response and methodology for estimation of model parameters. Models and methods for spatially co...
Megan Dailey Higgs, Jennifer A. Hoeting
JMLR
2002
73views more  JMLR 2002»
13 years 7 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
ICASSP
2011
IEEE
12 years 11 months ago
A Bernoulli-Gaussian model for gene factor analysis
This paper investigates a Bayesian model and a Markov chain Monte Carlo (MCMC) algorithm for gene factor analysis. Each sample in the dataset is decomposed as a linear combination...
Cecile Bazot, Nicolas Dobigeon, Jean-Yves Tournere...