For classification purpose, we propose a discriminative model selection method to optimize the orders of all classes. Based on the GMMs initialized in some way, ...
In this paper, we propose a fast discriminative model selection method for GMM for classification, which determines the number of components in EM training by ...
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This paper proposes a discriminative method to select GMM structures for pattern classification. We introduce a GMM structure selection criterion based on a ...
In this paper, we derive classifiers which are winner-take-all (WTA) approximations to a Bayes classifier with Gaussian mixtures for.
This example shows that model selection can be performed with Gaussian Mixture Models (GMM) using information-theory criteria.
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Abstract. We show that a classifier based on Gaussian mixture models (GMM) can be trained dis- criminatively to improve accuracy. We de-.
Jan 6, 2017 · The building blocks of LDA and GMM are similar ie both Gaussian but there are many differences. In GMM we are trying to estimate a distribution.
This paper proposes a discriminative method to select GMM structures for pattern classification. We introduce a GMM structure selection criterion based on a ...
In this paper, we propose a discriminative GMM structure selection method for pattern classification through embedding a discriminative learning criterion into ...
Discriminative structure selection method of Gaussian Mixture Models with its application to handwritten digit recognition · 21 Citations · 45 References.
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