With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc.,...
Background: Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or ‘workflow’, is a well-defined protocol, with a specific structure defin...
Many temporal applications like planning and scheduling can be viewed as special cases of the numeric and symbolic temporal constraint satisfaction problem. Thus we have developed ...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
lem of inferring termination from such abstract information is not the halting problem for programs and may well be decidable. If this is the case, the decision algorithm forms a &...