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ICASSP
2010
IEEE
13 years 7 months ago
GHT based implementation of the expectation maximization for mixtures of multi-Gaussians and its applications to video tracking
In this work, the problem of the estimation of parameters in case of mixtures of models composed by the sum of multiple Gaussians is considered. It will be shown how this estimati...
Francesco Monti, Carlo S. Regazzoni
INTERSPEECH
2010
13 years 3 months ago
Semi-supervised training of Gaussian mixture models by conditional entropy minimization
In this paper, we propose a new semi-supervised training method for Gaussian Mixture Models. We add a conditional entropy minimizer to the maximum mutual information criteria, whi...
Jui-Ting Huang, Mark Hasegawa-Johnson
JMLR
2010
129views more  JMLR 2010»
13 years 3 months ago
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...

Book
778views
15 years 7 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
CVPR
2007
IEEE
14 years 11 months ago
An MRF and Gaussian Curvature Based Shape Representation for Shape Matching
Matching and registration of shapes is a key issue in Computer Vision, Pattern Recognition, and Medical Image Analysis. This paper presents a shape representation framework based ...
Pengdong Xiao, Nick Barnes, Tibério S. Caet...