In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
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...
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...