This comprehensive treatment of network information theory and its applications provides
the first unified coverage of both classical and recent results. With an approach that …

This report reviews the conceptual and theoretical links between Granger causality and
directed information theory. We begin with a short historical tour of Granger causality …

Working under a model of privacy in which data remain private even from the statistician, we
study the tradeoff between privacy guarantees and the risk of the resulting statistical …

Advances in recording technologies have given neuroscience researchers access to large
amounts of data, in particular, simultaneous, individual recordings of large groups of …

We propose a graphical model for representing networks of stochastic processes, the
minimal generative model graph. It is based on reduced factorizations of the joint distribution …

Although users can obtain various services by sharing their location information online with
location-based service providers, it reveals sensitive information about users. However …

We consider a discrete-time linear-quadratic-Gaussian (LQG) control problem, in which
Massey's directed information from the observed output of the plant to the control input is …

Four estimators of the directed information rate between a pair of jointly stationary ergodic
finite-alphabet processes are proposed, based on universal probability assignments. The …

This work develops a new method for estimating and optimizing the directed information rate
between two jointly stationary and ergodic stochastic processes. Building upon recent …

The Cheeger inequality for undirected graphs, which relates the conductance of an
undirected graph and the second smallest eigenvalue of its normalized Laplacian, is a …