Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Recent efforts in the Conceptual Modelling community have been devoted to properly capturing time-varying information, and several proposals of temporally enhanced Entity-Relation...
This paper describes an approach for application specific conflict prevention based on model-driven refinement of policies prior to deployment. Central to the approach is an algori...
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
Abstract Many compiler optimization techniques depend on the ability to calculate the number of elements that satisfy certain conditions. If these conditions can be represented by ...
Sven Verdoolaege, Rachid Seghir, Kristof Beyls, Vi...