The vast majority of research projects involving Grid Computing have focused on the development and standardization of the middleware that allows Grids to function. Despite the ma...
Santiago Pena, Dayong Huang, Zhou Lei, Gabrielle A...
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
In this paper we develop a two stage algorithm for scheduling call centers with strict SLAs and arrival rate uncertainty. The first cut schedule can be developed in less than a mi...
We present a model of adaptive side-channel attacks which we combine with information-theoretic metrics to quantify the information revealed to an attacker. This allows us to expr...