—In this paper we present an Information Theoretic Estimator for the number of sources mutually disjoint in a linear mixing model. The approach follows the Minimum Description Le...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
This paper aims at deriving a relationship between minimum mean square error (MMSE) based source separation and independent component analysis (ICA) based on the Kullback-Leibler ...
This work proposes to generalize the method of cokriging when data are spatially sampled curves. A spatial functional linear model is constructed including spatial dependencies be...
David Nerini, Pascal Monestiez, Claude Manté...
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...