—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
We study convergence properties of empirical minimization of a stochastic strongly convex objective, where the stochastic component is linear. We show that the value attained by t...
In this work we revisit the Mumford-Shah functional, one of the most studied variational approaches to image segmentation. The contribution of this paper is to propose an algorith...
Thomas Pock, Daniel Cremers, Horst Bischof, Antoni...
Abstract We tackle the problem of detecting occluded regions in a video stream. Under assumptions of Lambertian reflection and static illumination, the task can be posed as a vari...
Abstract-- New methods for model validation of continuoustime nonlinear systems with uncertain parameters are presented in this paper. The methods employ functions of state-paramet...