Facets
of Entropy
By

Prof.
Raymond W.H. Yeung

Professor
of Information Engineering, CUHK







Date:
June 22, 2009 (Monday) 
Time:
4:30p.m.  5:30 p.m. 
Venue:
Rm. 1009, William M. W. Mong Engineering Building,
CUHK 
Abstract
:
Constraints on the entropy function are sometimes
referred to as the laws of information theory. For
a long time, the submodular inequalities, or equivalently
the nonnegativity of the Shannon information measures,
are the only known constraints. Inequalities that
are implied by the submodular inequality are categorically
referred to as Shannontype inequalities. If the number
of random variables is fixed, a Shannontype inequality
can in principle be verified by a linear program known
as ITIP.
A
nonShannontype inequality is a constraint on the
entropy function which is not implied by the submodular
inequality. In the late 1990's, the discovery of a
few such inequalities revealed that Shannontype inequalities
alone do not constitute a complete set of constraints
on the entropy function.
In the past decade, connections between the entropy
function and a number of fields in information science,
mathematics, and physics have been established. These
fields include probability theory, network coding,
combinatorics, group theory, Kolmogorov complexity,
matrix theory, and quantum mechanics. This talk is
an attempt to present a picture for the many facets
of the entropy function. 