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» Bayesian Approaches to Gaussian Mixture Modeling
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ICML
2008
IEEE
14 years 9 months ago
Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity
Causal analysis of continuous-valued variables typically uses either autoregressive models or linear Gaussian Bayesian networks with instantaneous effects. Estimation of Gaussian ...
Aapo Hyvärinen, Patrik O. Hoyer, Shohei Shimi...
TNN
2008
128views more  TNN 2008»
13 years 8 months ago
A Hybrid Technique for Blind Separation of Non-Gaussian and Time-Correlated Sources Using a Multicomponent Approach
Blind inversion of a linear and instantaneous mixture of source signals is a problem often encountered in many signal processing applications. Efficient FastICA (EFICA) offers an ...
Petr Tichavský, Zbynek Koldovský, Ar...
IDA
2009
Springer
14 years 3 months ago
Probabilistic Formulation of Independent Vector Analysis Using Complex Gaussian Scale Mixtures
We propose a probabilistic model for the Independent Vector Analysis approach to blind deconvolution and derive an asymptotic Newton method to estimate the model by Maximum Likelih...
Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Mak...
ICIP
2000
IEEE
14 years 1 months ago
Modelling Profiles with a Mixture of Gaussians
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data,...
James Orwell, Darrel Greenhill, Jonathan D. Rymel,...
TCSV
2010
13 years 3 months ago
Image and Video Segmentation by Combining Unsupervised Generalized Gaussian Mixture Modeling and Feature Selection
In this letter, we propose a clustering model that efficiently mitigates image and video under/over-segmentation by combining generalized Gaussian mixture modeling and feature sele...
Mohand Saïd Allili, Djemel Ziou, Nizar Bougui...