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Comment by sabraham | Hacker News Reader

PGMs don't get the same sexy treatment that ML and AI seem to get in pop science articles, so it may be worth stating explicitly that they're very much used in ML and are intellectually fascinating in their own right. A graphical model can fully describe the distribution and dependences of a model. Why this is important: a graphical model makes it very easy to give a computer your model, and there has been great success over the past two decades in doing just this [1].

Further, Daphne Koller is a serious force in the field, and seems to be a pretty good supervisor, so I'm guessing/hoping she is an interesting/engaging lecturer as well. Though, Stanford CS/Stats students are more able to comment on this last point.

[1] http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/contents.shtml

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I'm I right to surmise that "graphical" refers to graphs rather than "graphics", or was that just one example in the video?

Yes, "graphical models" are a formalism for representing and reasoning about probability distributions using graphs.

Yes. Confusing, isn't it?

For me, as non native English speaker is more confusing.

In Portuguese we say grafos(graphs) and gráficos, when we refer to pics and images. And when I read something in English, I wonder if its graphs referring to maths or to pics.

> Further, Daphne Koller is a serious force in the field, and seems to be a pretty good supervisor, so I'm guessing/hoping she is an interesting/engaging lecturer as well. Though, Stanford CS/Stats students are more able to comment on this last point.

What's the source? She's a brilliant researcher, but I've heard quite the opposite about her attitude towards human relationships...

Ah, so I used a 2-degree heuristic to come to that conclusion--I haven't had any first hand experience with her, nor do I have contact with her former students. A few stats professors independently recommended her to me as a supervisor, her students seem to do well, and her research page is more welcoming than most (versus, say Ullman's page: http://infolab.stanford.edu/~ullman/ or say, read Brian Ripley's posts on the R mailing list). The one thing I'd add: my experience has been that academics generally have less empathy than others; I'd be interested to hear from old students how she compares to other faculty.

I know a lot of Daphne's former and current students and she seems to be a great advisor who genuinely cares about producing both excellent research and top quality research talent.

Further, in the department, I think she is one of the people who cares most about teaching. She runs the undergraduate summer research program. She re-does her class on PGMs substantially almost every time she teaches it to try to make it better. (Though such a high rate of change may or may not be a good idea.) Daphne is almost certainly one of the key people behind the *-class effort at Stanford CS.

For those with a negative impression of Daphne, my guess is just that they are misinterpreting her directness. If she thinks you're wrong, or you're doing the wrong research, you'll know about it.

(Also, Ullman is one of the nicest people in the department in person, which is crazy given that he wrote the standard texts in compilers, databases, and arguably automata. He's emeritus these days though.)

Thanks for the insights! I appreciate it.

I did research with Daphne (and co-authored a paper with her) in my senior year of undergrad, and she demanded a high standard of work, yes, but she was an excellent supervisor. Everybody knows how brilliant she is, but she also put a lot of effort into teaching my (also undergrad) project partner and I about how to formulate a research problem, how to do research, and how to present research. The primary concern appeared to be our personal growth, not the research machine (though that's not to say that the research wasn't important).

Working with her was one of the highlights of my undergrad education, and her class was great, too.

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