An m-sample semiparametric model in which the ratio of m - 1 probability density functions with respect to the mth is of a known parametric form without reference to any parametri...
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
In the context of code coupling, efficient data redistribution is a crucial issue to reach high-performances. However, most of the works in this area have limited their studies to ...
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Abstract. In the context of multimedia data analysis, it is often necessary to understand what happens in a scene, which can rely on detecting and tracking the different moving obj...