abstract: In Part II, we build upon the variational framework introduced in the first lecture with a discussion of more advanced topics. In particular, we cover recent work on the connections between message-passing and classical relaxation methods from combinatorial optimization, including linear programming and semidefinite relaxations. We also discuss the learning-theoretic problem of model estimation, and the role of variational methods in this setting.