Exponential Family Graphical Models: Inference, Learning and
Convexity
Jason K. Johnson and O. Patrick Kreidl
The objective of this presentation is to provide an overview of
exponential family graphical models and to introduce the following
topics: (i) exact recursive inference methods, (ii) model
identification methods and (iii) the role of convex duality in these
problems. We also touch upon some advanced topics, including
approximate inference and model structure estimation.