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» Robust Bayesian Mixture Modelling
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IJCAI
2007
13 years 6 months ago
Collapsed Variational Dirichlet Process Mixture Models
Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
Kenichi Kurihara, Max Welling, Yee Whye Teh
CVPR
2008
IEEE
14 years 7 months ago
Robust estimation of gaussian mixtures from noisy input data
We propose a variational bayes approach to the problem of robust estimation of gaussian mixtures from noisy input data. The proposed algorithm explicitly takes into account the un...
Shaobo Hou, Aphrodite Galata
TIP
2008
157views more  TIP 2008»
13 years 5 months ago
Robust Face Tracking via Collaboration of Generic and Specific Models
Significant appearance changes of objects under different orientations could cause loss of tracking, "drifting." In this paper, we present a collaborative tracking framew...
Peng Wang, Qiang Ji
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 5 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...
CSDA
2010
208views more  CSDA 2010»
13 years 5 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...