We introduce a graphical framework for Bayesian inference that is sufficiently general to accommodate not just the standard case but also recent proposals for a theory of quantum...
Privacy-Preserving Data Re-publishing (PPDR) deals with publishing microdata in dynamic scenarios. Due to privacy concerns, data must be disguised before being published. Research...
In this paper we investigate the fault diagnosis problem in IP networks. We provide a lower bound on the average number of probes per edge using variational inference technique pro...
Rajesh Narasimha, Souvik Dihidar, Chuanyi Ji, Stev...
In probabilistics, reasoning at optimum entropy (ME-reasoning) has proved to be a most sound and consistent method for inference. This paper investigates its properties in the fram...
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...