Often the time derivative of a measured variable is of as much interest as the variable itself. For a growing population of biological cells, for example, the population’s growth rate is typically ...

Matrix-variate Gaussian graphical models (GGM) have been widely used for modeling matrix-variate data. Since the support of sparse precision matrix represents the conditional independence graph among ...

Graphical Gaussian models with edge and vertex symmetries were introduced by Højsgaard & Lauritzen (2008), who gave an algorithm for computing the maximum likelihood estimate of the precision matrix ...

One of the fundamental operations in machine learning is computing the inverse of a square matrix. But not all matrices have an inverse. The most common way to check if a matrix has an inverse or not ...

Abstract: Detectors based on matrix information geometry have been developed recently and demonstrated advantages against conventional methods for detection of targets within nonhomogeneous clutter ...