In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
We address covariance estimation under mean-squared loss in the Gaussian setting. Specifically, we consider shrinkage methods which are suitable for high dimensional problems wit...
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
The Median-Rational Hybrid Filter (MRHF) has been recently introduced [1][2] as a new class of nonlinear filters and successfully applied to image filtering problems. The main cha...
Lazhar Khriji, Giuseppe Bernacchia, Moncef Gabbouj...
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...