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ICPR
2008
IEEE
14 years 4 months ago
Parameter-based reduction of Gaussian mixture models with a variational-Bayes approach
This paper 1 proposes a technique for simplifying a given Gaussian mixture model, i.e. reformulating the density in a more parcimonious manner, if possible (less Gaussian componen...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
GFKL
2005
Springer
141views Data Mining» more  GFKL 2005»
14 years 3 months ago
On External Indices for Mixtures: Validating Mixtures of Genes
Mixture models represent results of gene expression cluster analysis in a more natural way than ’hard’ partitions. This is also true for the representation of gene labels, such...
Ivan G. Costa, Alexander Schliep
ESANN
2007
13 years 11 months ago
Mixtures of robust probabilistic principal component analyzers
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
Cédric Archambeau, Nicolas Delannay, Michel...
NIPS
2004
13 years 11 months ago
Hierarchical Clustering of a Mixture Model
In this paper we propose an efficient algorithm for reducing a large mixture of Gaussians into a smaller mixture while still preserving the component structure of the original mod...
Jacob Goldberger, Sam T. Roweis