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ACL
2012
11 years 8 months ago
Improving the IBM Alignment Models Using Variational Bayes
Bayesian approaches have been shown to reduce the amount of overfitting that occurs when running the EM algorithm, by placing prior probabilities on the model parameters. We appl...
Darcey Riley, Daniel Gildea
NECO
2007
129views more  NECO 2007»
13 years 5 months ago
Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
Shinichi Nakajima, Sumio Watanabe
ICDAR
2009
IEEE
13 years 3 months ago
A Variational Bayes Method for Handwritten Text Line Segmentation
Text line segmentation in unconstrained handwritten documents remains a challenge because handwritten text lines are multi-skewed and not obviously separated. This paper presents ...
Fei Yin, Cheng-Lin Liu
ICASSP
2011
IEEE
12 years 9 months ago
The transformed Variational Bayes approximation
The purpose of this paper is to develop parameter transformation strategies that improve the accuracy of the Variational Bayes (VB) approximation. The idea is to find a transform...
Viet Hung Tran, Anthony Quinn
ICPR
2008
IEEE
14 years 12 days ago
Parameter-based reduction of Gaussian mixture models with a variational-Bayes approach
This paper 1 proposes a technique for simplifying a given Gaussian mixture model, i.e. reformulating the density in a more parcimonious manner, if possible (less Gaussian componen...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne