We propose a series of methods to represent the evolution of a field of science at different levels: namely micro, meso and macro levels. We use a previously introduced asymmetric...
High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible ...
Sahand Negahban, Pradeep Ravikumar, Martin J. Wain...
This paper offers several contributions for separation of duty (SoD) administration in role-based access control (RBAC) systems. We first introduce a new formal framework, based o...
Alessandro Colantonio, Roberto Di Pietro, Alberto ...
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
In this paper, we investigate cyclic sequences which contain as elements all k-subsets of {0, 1, . . . , n-1} exactly once such that the unions of any two consecutive k-subsets of...