Dataflow computation models enable simpler and more efficient management of the memory hierarchy - a key barrier to the performance of many parallel programs. This paper describes...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Interpretation interpretation is a theory of effective abstraction and/or approximation of discrete mathematical structures as found in the semantics of programming languages, mod...
Abstract. We present a well-founded semantics for deductive objectoriented database (dood) languages by applying the alternating- xpoint characterization of the well-founded model ...
Since several years, ubiquitous computing and pervasive computing has emerged and, in particular, context-aware computing. Using mobile devices, the context is perpetually evolvin...