Gauss mixtures have gained popularity in statistics and statistical signal processing applications for a variety of reasons, including their ability to well approximatea large cla...
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coef?cients of an arbitrary li...
Karen O. Egiazarian, Alessandro Foi, Vladimir Katk...
Abstract. Hyperspectral imagery is a new type of high-dimensional image data which is now used in many Earth-based and planetary exploration applications. Many efforts have been d...
Efficient algorithms for compressing geometric data have been widely developed in the recent years, but they are mainly designed for closed polyhedral surfaces which are manifold ...