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» Density Estimation by Mixture Models with Smoothing Priors
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ICASSP
2010
IEEE
13 years 8 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock
NIPS
2007
13 years 10 months ago
Learning with Tree-Averaged Densities and Distributions
We utilize the ensemble of trees framework, a tractable mixture over superexponential number of tree-structured distributions [1], to develop a new model for multivariate density ...
Sergey Kirshner
IBPRIA
2007
Springer
14 years 2 months ago
Bayesian Oil Spill Segmentation of SAR Images Via Graph Cuts
Abstract. This paper extends and generalizes the Bayesian semisupervised segmentation algorithm [1] for oil spill detection using SAR images. In the base algorithm on which we buil...
Sónia Pelizzari, José M. Bioucas-Dia...
ESANN
2003
13 years 10 months ago
On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on...
Cédric Archambeau, John Aldo Lee, Michel Ve...
ICMLA
2008
13 years 10 months ago
Semi-supervised IFA with Prior Knowledge on the Mixing Process: An Application to a Railway Device Diagnosis
Independent Factor Analysis (IFA) is a well known method used to recover independent components from their linear observed mixtures without any knowledge on the mixing process. Su...
Etienne Côme, Zohra Leila Cherfi, Latifa Ouk...