If you are interested in learning this topic, do not go directly to Koller/Friedman book - it sure contains a lot of material but its presentation is not well integrated (just look at the topic dependency graph at the beginning).
A much more cohesive introduction would be Michael Jordan's book draft that has been floating around for nearly a decade now. You can find some of the older versions online, e.g. http://www.cs.cmu.edu/~lebanon/pub/book
Go directly to chapter 5 to see how the language of PGMs can help to clarify a lot of standard material in stats and ML.
And for a nice overview of how factor graphs, when considered generally, really can capture arbitrary dependencies I would check out "Extending factor graphs so as to unify directed and undirected graphical models" http://uai.sis.pitt.edu/papers/03/p257-frey.pdf.
Was this (Jordan's) book published? If yes, what is it called? He seems to have a couple of other books on Graphical models, but the contents of those book don't line up with the ones at the link above.
This book does not exist as a published volume, at least not in the way it is presented in this draft. This is why it tends to circulate as a draft, rather than as (say) an Amazon link.
Thank You. I spent some time looking for it. And if anyone who has an up to date draft wants to send me a copy, my email is in my profile, Thanks in Advance :).
A much more cohesive introduction would be Michael Jordan's book draft that has been floating around for nearly a decade now. You can find some of the older versions online, e.g. http://www.cs.cmu.edu/~lebanon/pub/book
Go directly to chapter 5 to see how the language of PGMs can help to clarify a lot of standard material in stats and ML.