Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
In this work we present a novel approach for learning nonhomogenous textures without facing the unlearning problem. Our learning method mimics the human behavior of selective lear...
This paper presents a study aimed to the realization of a novel
multiresolution registration framework. The transformation
function is computed iteratively as a composition of lo...
Popularity of mobile devices is accompanied by widespread security problems, such as MAC address spoofing in wireless networks. We propose a probabilistic approach to temporal an...
Abstract. We present an exploratory method for simultaneous parcellation of multisubject fMRI data into functionally coherent areas. The method is based on a solely functional repr...