Monday, November 13, 2017
Freie Universität Berlin
Institut für Informatik
Takustr. 9
14195 Berlin
room 005
Lecture - 14:15
Abstract:
All finite graphs satisfy the two properties mentioned in the title. I
will explain what I mean by this, and speculate on generalizations and
interconnections. This talk will be non-technical: Nothing will be
assumed beyond basic linear algebra.
Colloquium - 16:00
Abstract:
Maximum entropy probability distributions are important
for information theory and relate directly to exponential families in
statistics. Having the property of maximizing entropy can be used to
define a discrete analogue of the classical continuous Gaussian
distribution. We present a parametrization of such a density using the
Riemann Theta function, use it to derive fundamental properties which
include computing its characteristic function, and exhibit connections
to the study of abelian varieties. This is joint work with Daniele
Agostini (HU Berlin).