School of Mathematical Sciences

Learning, prediction and causation with graphical models menu

Learning, prediction and causation with graphical models

Speaker: 
Guy FreemanUniversity of Warwick
Date/Time: 
Thu, 28/10/2010 - 17:30
Room: 
M203
Seminar series: 

Graphical models provide a very promising avenue for making sense
of large, complex datasets. In this talk I review strategies for
learning Bayesian networks, the most popular graphical models currently
in use, and introduce a new graphical model, the chain event graph,
which is an improvement on using the Bayes net in many cases but
which introduces its own challenges for learning, prediction and
causation.