We study the clustering problem on graphs: it is known that if there are two underlying clusters, then signs of eigenvector corresponding to second largest eigenvalue adjacency matrix can reliably reconstruct clusters. We argue vertices for which has and smallest entries, respectively, unusually strongly connected their own cluster more classified than rest. This be...

In the min-entropy approach to quantitative information flow, the leakage is defined in terms of a minimization problem, which, in case of large systems, can be computationally rather heavy. The same happens for the recently proposed generalization called g-vulnerability. In this paper we study the case in which the channel associated to the system can be decomposed into simpler channels, which...