This book is an evolution from my book A First Course in Information Theory published in
2002 when network coding was still at its infancy. The last few years have witnessed the …

The families of f-divergences (eg the Kullback-Leibler divergence) and Integral Probability
Metrics (eg total variation distance or maximum mean discrepancies) are widely used to …

This paper derives new bounds on the difference of the entropies of two discrete random
variables in terms of the local and total variation distances between their probability mass …

We consider the additional entropy production (EP) incurred by a fixed quantum or classical
process on some initial state ρ, above the minimum EP incurred by the same process on any …

This paper gives an algorithm for calculating posterior probabilities using thermodynamic
integration. The thermodynamic integration calculations are accomplished by annealing an …

We study the properties of quantum entropy and-capacity (regarded as a function of sets of
quantum states) in the infinite-dimensional case. We obtain conditions for the boundedness …

In this paper, some general properties of Shannon information measures are investigated
over sets of probability distributions with restricted marginals. Certain optimization problems …

Potential supply-net risk factors include capacity issues, currency volatility, design changes,
frequent changes in tax regulations, unsafe information systems, and port shutdowns. Such …

The Shannon information measures are well known to be continuous functions of the
probability distribution for a given finite alphabet. In this paper, however, we show that these …

Convergence properties of Shannon entropy are studied. In the differential setting, it is
known that weak convergence of probability measures (convergence in distribution) is not …