Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
We address distributed real-time applications represented by systems of non-preemptive dependent periodic tasks. This system is described by an acyclic directed graph. Because the...
This paper presents an approach to simulate complex hierarchical process chains resulting from large logistics networks in OMNeT++, a discrete event simulation environment designe...
Falko Bause, Peter Buchholz, Jan Kriege, Sebastian...
We consider the problem of query containment over an object data model derived from F-logic. F-logic has generated considerable interest commercially, in the academia, and within ...