Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
We consider mixtures of parametric densities on the positive reals with a normalized generalized gamma process (Brix, 1999) as mixing measure. This class of mixtures encompasses t...
Raffaele Argiento, Alessandra Guglielmi, Antonio P...
A major challenge for face recognition algorithms lies in the variance faces undergo while changing pose. This problem is typically addressed by building view dependent models bas...
The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...