In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
In this paper, a novel method to extend the grayscale histogram equalization (GHE) for color images in a multidimension is proposed. Unlike most current techniques, the proposed m...
I consider the problem of finding all the modes of a mixture of multivariate Gaussian distributions, which has applications in clustering and regression. I derive exact formulas f...
Multivariate Gaussian models are widely adopted in continuous Estimation of Distribution Algorithms (EDAs), and covariance matrix plays the essential role in guiding the evolution...
We investigate the use of an unsupervised artificial neural network to form a sparse representation of the underlying causes in a data set. By using fixed lateral connections that...