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» Advances in Mixture Models
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KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 10 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
TNN
2010
216views Management» more  TNN 2010»
13 years 4 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
CSDA
2010
208views more  CSDA 2010»
13 years 10 months ago
Bayesian density estimation and model selection using nonparametric hierarchical mixtures
We consider mixtures of parametric densities on the positive reals with a normalized generalized gamma process (Brix, 1999) as mixing measure. This class of mixtures encompasses t...
Raffaele Argiento, Alessandra Guglielmi, Antonio P...
ICPR
2000
IEEE
14 years 11 months ago
Growing Gaussian Mixture Models for Pose Invariant Face Recognition
A major challenge for face recognition algorithms lies in the variance faces undergo while changing pose. This problem is typically addressed by building view dependent models bas...
Ralph Gross, Jie Yang, Alex Waibel
NN
2002
Springer
161views Neural Networks» more  NN 2002»
13 years 9 months ago
AANN: an alternative to GMM for pattern recognition
The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...
B. Yegnanarayana, S. P. Kishore