In this paper we propose an efficient algorithm for reducing a large mixture of Gaussians into a smaller mixture while still preserving the component structure of the original mod...
: Kriging-based exploration strategies often rely on a single Ordinary Kriging model which parametric covariance kernel is selected a priori or on the basis of an initial data set....
A new hierarchical Bayesian model is proposed for image segmentation based on Gaussian mixture models (GMM) with a prior enforcing spatial smoothness. According to this prior, the...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
A recent neuro-spiking coding scheme for feature extraction from biosonar echoes of various plants is examined with a variety of stochastic classifiers. Feature vectors derived are...