today: ML presentations; Hinton; FOPI

[gusl]

Machine Learning presentations:
* Lots of bioinformatics stuff, which I understood nothing of.
* kutta's talk had a slide about "Lacerdian Multinoullis". (I coined the term "multinoulli" because "multinomial" sounds too much like "binomial". Kevin loved it, and has been pushing its usage since; he's promoting this term in his book)
* My presentation went well, it seems. kutta found it one of the clearest. Kevin only pointed out a minor flaw in a scatterplot, and made a suggestion to couple my 24 autoregressions. I'm really enjoying this project, though I occasionally worry about having to solve a difficult inference problem and running out of time.

Then I met with Geoff Hinton, which was biggest the flurry of ideas I've discussed in a really long time. I don't remember ever having such an idea-dense meeting. Time really flew, and I have a full page of notes.

After that, I attended the FOPI reading group. Thanks to my nitpickiness about people who use "d-separation equivalence" interchangeably with "distribution equivalence", we got into tangent in which I essentially gave my UAI talk to everyone there. I really enjoyed that.

Then I did my extra Vision homework; and researched¹ a paper on Soft Weight-Sharing to solve my problem (by guess who? Hinton!).

I'm getting used to these 12h days, and I don't mind it at all. :-)

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^{1 - what do you call it when you skim a paper, find the section you want, and read that section very thoroughly / several times? Did you "read" the paper?}

Comments

[bhudson.livejournal.com]

Did you "read" the paper?

You've probably read the paper more than almost anyone else who cites it.