Perfect Graphs And Graphical Modeling

This chapter reduces the inference problem in probabilistic graphical models to an equivalent maximum weight stable set problem on a graph. We discuss methods for recognizing when the latter problem can be solved efficiently by appealing to perfect graph theory. Furthermore, practical solvers based on convex programming and message-passing are presented.