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» Density Estimation Using Mixtures of Mixtures of Gaussians
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151
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TNN
2010
216views Management» more  TNN 2010»
14 years 8 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
146
Voted
PAKDD
2005
ACM
184views Data Mining» more  PAKDD 2005»
15 years 7 months ago
Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
Luo Si, Rong Jin
CVPR
2012
IEEE
13 years 4 months ago
Background modeling using adaptive pixelwise kernel variances in a hybrid feature space
Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussi...
Manjunath Narayana, Allen R. Hanson, Erik G. Learn...
115
Voted
ICASSP
2010
IEEE
15 years 2 months ago
Under-determined convolutive blind source separation using spatial covariance models
This paper deals with the problem of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency d...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...
ICIP
2001
IEEE
16 years 3 months ago
Minimum discrimination information clustering: modeling and quantization with Gauss mixtures
Gauss mixtures have gained popularity in statistics and statistical signal processing applications for a variety of reasons, including their ability to well approximatea large cla...
Robert M. Gray, John C. Young, Anuradha K. Aiyer