In this paper, we present a novel system modeling language which targets primarily the development of source-level multiprocessor memory aware optimizations. In contrast to previo...
Robert Pyka, Felipe Klein, Peter Marwedel, Stylian...
We investigate the complexity of performing updates on probabilistic XML data for various classes of probabilistic XML documents of different succinctness. We consider two elemen...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Computational models of motivation are tools that artificial agents can use to autonomously identify, prioritize, and select the goals they will pursue. Previous research has focu...
Belief propagation is a popular global optimization technique for many computer vision problems. However, it requires extensive computation due to the iterative message passing op...