We present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. Our formulation provides answers to...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
AbstractDeveloping wireless sensor networks can enable information gathering, information processing and reliable monitoring of a variety of environments for both civil and militar...
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need ...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales...