We show how well-known refinements of ordered resolution, in particular redundancy elimination and ordering constraints in combination with a selection function, can be used to obt...
We present two solutions for the scale selection problem in computer vision. The rst one is completely nonparametric and is based on the the adaptive estimation of the normalized ...
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
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...
: In a component-based development process the selection of components is an activity that takes place over multiple lifecycle phases that span from requirement specifications thro...