Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Abstract—In this paper we propose a novel statistical framework to model the impact of process variations on semiconductor circuits through the use of process sensitive test stru...
We develop a multi-stage stochastic programming model for international portfolio management in a dynamic setting. We model uncertainty in asset prices and exchange rates in terms...
We propose a framework where behavioural properties of finite-state systems modelled as graph transformation systems can be expressed and verified. The technique is based on the ...