We propose a model for the density of cross-spectral coefficients using Normal Variance Mean Mixtures. We show that this model density generalizes the corresponding marginal dens...
Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delg...
In this paper we study the problem of bivariate density estimation. The aim is to find a density function with the smallest number of local extreme values which is adequate with ...
Early estimation of defect density of a product is an important step towards the remediation of the problem associated with affordably guiding corrective actions in the software d...
Mark Sherriff, Nachiappan Nagappan, Laurie A. Will...
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distri...