—1 In this paper we present a stochastic model order reduction technique for interconnect extraction in the presence of process variabilities, i.e. variation-aware extraction. It...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
In this work, we investigate the security of anonymous wireless sensor networks. To lay down the foundations of a formal framework, we propose a new model for analyzing and evalua...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
Program dependence graphs are a well-established device to represent possible information flow in a program. Path conditions in dependence graphs have been proposed to express mo...