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UAI
2000
15 years 4 months ago
Minimum Message Length Clustering Using Gibbs Sampling
The K-Means and EM algorithms are popular in clustering and mixture modeling due to their simplicity and ease of implementation. However, they have several significant limitations...
Ian Davidson
TSP
2008
173views more  TSP 2008»
15 years 3 months ago
Gaussian Mixture Modeling by Exploiting the Mahalanobis Distance
In this paper, the expectation-maximization (EM) algorithm for Gaussian mixture modeling is improved via three statistical tests. The first test is a multivariate normality criteri...
Dimitrios Ververidis, Constantine Kotropoulos
JMLR
2010
129views more  JMLR 2010»
14 years 10 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
14 years 6 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs

Publication
1851views
17 years 4 months ago
Cerebrovascular Segmentation from TOF Using Stochastic Models
In this paper, we present an automatic statistical approach for extracting 3D blood vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) data. The voxels of the d...
M. Sabry Hassouna, Aly A. Farag, Stephen Hushek, T...