Humans know how to reason based on cause and effect, but cause and effect is not enough to draw conclusions due to the problem of imperfect information and uncertainty. To resol...
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efficient reasoning mechanisms of Bayesian Networks with the...
We present a report on work in progress on certain aspects of a programme of research concerned with building formal, mathematical models both for aspects of the computational pro...
We introduce an extension of linear constraints, called linearrange constraints, which allows for (meta-)reasoning about the approximation width of variables. Semantics for linear...
In this paper, we propose a formal analysis approach to estimate the expected (average) data cache access time of an application across all possible program inputs. Towards this g...