We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
Color image demosaicking is a key process in the digital imaging pipeline. In this paper, we present a rigorous treatment of a classical demosaicking algorithm based on alternatin...
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Objective: Currently, visualization support for patient data analysis is mostly limited to the representation of directly measured data. Contextual information on performed treatm...
The gramian approximation methods have been proposed recently to overcome the high computing costs of classical balanced truncation based reduction methods. But those methods typi...