Given n discrete random variables, its entropy vector is the 2^n - 1-dimensional vector obtained from the joint entropies of all non-empty subsets of the random variables. It is well known that there is a close relation between such an entropy vector and a certain group-characterizable vector obtained from a finite group and n of its subgroups; indeed, roughly speaking, knowing the region of all such group-characterizable vectors is equivalent to knowing the region of all entropy vectors. This correspondence may be useful for characterizing the space of entropic vectors and for designing network codes. If one restricts attention to abelian groups then not all entropy vectors can be obtained. This is an explanation for the fact shown by Doug...
AbstractWe show that the classical notion of entropy of a finitely generated group G as introduced b...
Entropy inequalities play a central role in proving converse coding theorems for network information...
This dissertation takes a step toward a general framework for solving network information theory pro...
Given n discrete random variables, its entropy vector is the 2^n - 1-dimensional vector obtained fro...
It is well known that there is a one-to-one correspondence between the entropy vector of a collecti...
An entropic vector is a 2n - 1 dimensional vector collecting all the possible joint entropies of n d...
Linear rank inequalities in 4 subspaces are characterized by Shannon-type inequalities and the Ingle...
summary:The entropy region is a fundamental object of study in mathematics, statistics, and informat...
The study of codes, classically motivated by the need to communicate information reliably in the pre...
In principle, network codes derived from non-Abelian groups can be used to attain every point in the...
This thesis is dedicated to the study of information inequalities and quasi-uniform codes using grou...
A set of quasi-uniform random variables X1,…,Xn may be generated from a finite group G and n of its ...
Abstract — In this paper, we show that random variables mapped under group homomorphisms from a unif...
Given n (discrete or continuous) random variables X_i, the (2^n – 1)-dimensional vector obtained by ...
We show that a large class of network information theory problems can be cast as convex optimization...
AbstractWe show that the classical notion of entropy of a finitely generated group G as introduced b...
Entropy inequalities play a central role in proving converse coding theorems for network information...
This dissertation takes a step toward a general framework for solving network information theory pro...
Given n discrete random variables, its entropy vector is the 2^n - 1-dimensional vector obtained fro...
It is well known that there is a one-to-one correspondence between the entropy vector of a collecti...
An entropic vector is a 2n - 1 dimensional vector collecting all the possible joint entropies of n d...
Linear rank inequalities in 4 subspaces are characterized by Shannon-type inequalities and the Ingle...
summary:The entropy region is a fundamental object of study in mathematics, statistics, and informat...
The study of codes, classically motivated by the need to communicate information reliably in the pre...
In principle, network codes derived from non-Abelian groups can be used to attain every point in the...
This thesis is dedicated to the study of information inequalities and quasi-uniform codes using grou...
A set of quasi-uniform random variables X1,…,Xn may be generated from a finite group G and n of its ...
Abstract — In this paper, we show that random variables mapped under group homomorphisms from a unif...
Given n (discrete or continuous) random variables X_i, the (2^n – 1)-dimensional vector obtained by ...
We show that a large class of network information theory problems can be cast as convex optimization...
AbstractWe show that the classical notion of entropy of a finitely generated group G as introduced b...
Entropy inequalities play a central role in proving converse coding theorems for network information...
This dissertation takes a step toward a general framework for solving network information theory pro...