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» Learning Mixtures of Gaussians
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IJON
2006
99views more  IJON 2006»
14 years 10 months ago
Learning vector quantization: The dynamics of winner-takes-all algorithms
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
Michael Biehl, Anarta Ghosh, Barbara Hammer
ESANN
2004
15 years 2 days ago
Robust Bayesian Mixture Modelling
Abstract. Bayesian approaches to density estimation and clustering using mixture distributions allow the automatic determination of the number of components in the mixture. Previou...
Christopher M. Bishop, Markus Svensén
ICDM
2006
IEEE
145views Data Mining» more  ICDM 2006»
15 years 4 months ago
Stability Region Based Expectation Maximization for Model-based Clustering
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
ICPR
2002
IEEE
15 years 11 months ago
Context-Sensitive Bayesian Classifiers and Application to Mouse Pressure Pattern Classification
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
Yuan (Alan) Qi, Rosalind W. Picard
ICPR
2010
IEEE
15 years 5 months ago
Joint Image GMM and Shading MAP Estimation
We consider a simple statistical model of the image, in which the image is represented as a sum of two parts: one part is explained by an i.i.d. color Gaussian mixture and the oth...
Alexander Shekhovtsov, Vaclav Hlavac