A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization for solving hybrid Bayesian networks. Any probability density function can be approximated...
Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
This paper studies a hierarchical Bayesian model for nonlinear hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are polynomial functions of li...
Yoann Altmann, Abderrahim Halimi, Nicolas Dobigeon...