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» On Fitting Mixture Models
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IJCNN
2006
IEEE
14 years 4 months ago
Automated Model Selection (AMS) on Finite Mixtures: A Theoretical Analysis
— From the Bayesian Ying-Yang (BYY) harmony learning theory, a harmony function has been developed for finite mixtures with a novel property that its maximization can make model...
Jinwen Ma
ICIP
2010
IEEE
13 years 8 months ago
Gaussian mixture models for spots in microscopy using a new split/merge em algorithm
In confocal microscopy imaging, target objects are labeled with fluorescent markers in the living specimen, and usually appear as spots in the observed images. Spot detection and ...
Kangyu Pan, Anil C. Kokaram, Jens Hillebrand, Mani...
ICPR
2010
IEEE
13 years 8 months ago
Information Theoretic Expectation Maximization Based Gaussian Mixture Modeling for Speaker Verification
The expectation maximization (EM) algorithm is widely used in the Gaussian mixture model (GMM) as the state-of-art statistical modeling technique. Like the classical EM method, th...
Sheeraz Memon, Margaret Lech, Namunu Chinthaka Mad...
AAAI
2010
13 years 11 months ago
Gaussian Mixture Model with Local Consistency
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
Jialu Liu, Deng Cai, Xiaofei He
TSP
2008
173views more  TSP 2008»
13 years 10 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