We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
In this paper, we propose how the parameter distributions of multilinear geometric entities can be dualised. The dualisation concern, for example, the parameter distributions of c...
Abstract. This paper investigates the problem of autonomously allocating a large number of independent, equal sized tasks on a distributed heterogeneous grid-like platform, using o...
Our current research into programming models for parallel web services composition is targeted at providing mechanisms for obtaining higher throughput for large scale compute and ...
Peter M. Kelly, Paul D. Coddington, Andrew L. Wend...
Visualization is a powerful tool for analysing data and presenting results in science, engineering and medicine. This paper reviews ways in which it can be used in distributed and...
Ken Brodlie, David A. Duce, Julian R. Gallop, J. P...