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» Modelling Profiles with a Mixture of Gaussians
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CSDA
2007
134views more  CSDA 2007»
13 years 8 months ago
Variational approximations in Bayesian model selection for finite mixture distributions
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
Clare A. McGrory, D. M. Titterington
ICIP
2009
IEEE
14 years 9 months ago
Joint Recovery And Segmentation Of Polarimetric Images Using A Compound Mrf And Mixture Modeling
We propose a new approach for the restoration of polarimetric Stokes images, capable of simultaneously segmenting and restoring the images. In order to easily handle the admissibi...
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
14 years 8 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 7 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
PRL
2007
154views more  PRL 2007»
13 years 7 months ago
Regularized mixture discriminant analysis
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
Zohar Halbe, Mayer Aladjem