We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
In this paper we describe an online/incremental linear binary classifier based on an interesting approach to estimate the Fisher subspace. The proposed method allows to deal with ...
Alessandro Rozza, Gabriele Lombardi, Marco Rosa, E...