In this paper we present the theoretical setting for the closed form solutions to the multiview constraints of curves and surfaces observed by the motion of a camera in a scene. We...
— Systolic online algorithms for the multiplication of univariate polynomials and of multiple precision integers are synthesised using a novel method based on the following funct...
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Sparse regression is the problem of selecting a parsimonious subset of all available regressors for an efficient prediction of a target variable. We consider a general setting in w...
Reduced rank regression (RRR) has found application in various fields of signal processing. In this paper we propose a novel extension of the RRR model which we call sparse varia...