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ICPR
2008
IEEE
10 years 3 months ago
Component-wise parameter smoothing for learning mixture models
In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
Bala Rajaratnam, Chandan K. Reddy
NECO
1998
119views more  NECO 1998»
9 years 2 months ago
Density Estimation by Mixture Models with Smoothing Priors
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Akio Utsugi
ICPR
2010
IEEE
9 years 9 months ago
Joint Image GMM and Shading MAP Estimation
We consider a simple statistical model of the image, in which the image is represented as a sum of two parts: one part is explained by an i.i.d. color Gaussian mixture and the oth...
Alexander Shekhovtsov, Vaclav Hlavac
ICASSP
2009
IEEE
9 years 9 months ago
A variational EM algorithm for learning eigenvoice parameters in mixed signals
We derive an ef´Čücient learning algorithm for model-based source separation for use on single channel speech mixtures where the precise source characteristics are not known a pri...
Ron J. Weiss, Daniel P. W. Ellis
PAMI
2006
215views more  PAMI 2006»
9 years 2 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
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