Monthly Archives: November 2009

November 24, 2009 · 1:12 am

Machine Translation and the Porpoise Corpus

I might have mentioned that I got to do some world traveling for my work recently. Seeing rural Tanzania was an experience that I still don’t really have good words to describe. But this is not a post about that. This is a post about a sticky idea I got stuck on in some science fiction I was reading during my multi-day to and fro travel.

On my around-the-world-in-4.5-days journey, I read the Jewish feminist sci-fi novel He, She, and It by Marge Piercy. It’s got a classic hard AI theme, about a robot that is so, so human… I’d recommend it. But dilemmas of whether a robot can make a minyon in the reform tradition of 2059 has not stuck in my mind the way this one line about whales has: Continue reading →

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November 22, 2009 · 7:15 pm

Paper rejected, Cheer Up with Baby Animals

Too bad for me, my first global health paper will have to be revised and resubmitted. In addition to some more substantive objections, the negative reviewer said “It is unclear what software was used to carry out the Bayesian estimation by MCMC. This is not possible in STATA and would be extremely difficult in the scripting language, Python.” It was difficult in Python! I doubt that any software would make it much easier, though.

To cheer myself up, I’ve been looking into the newest fads in pets: robotic hamsters and teacup pigs.

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November 16, 2009 · 11:33 pm

Post-doc Ops

Would you like to work with me applying computational algorithms to challenges in global health metrics? Then apply for the IHME post-graduate fellowship. Deadline is Feb 15.

(There is also a “pre-graduate” version, for those who have not started graduate school yet.)

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November 14, 2009 · 8:21 pm

Clustering with Shallow Trees

I’m updating my CV, and that reminded me that I meant to promote this cool clustering technique that I was a little bit involved in, Clustering With Shallow Trees.

This goes way back to about half-way through my post-doc at MSR, when statistical physicist Riccardo Zecchina was visiting for a semester, and was teaching me about all of the “intractable” optimization problems that he can solve using his panoply of propagation algorithms. In particular, he was working on algorithms for certain types of steiner tree optimization, and he had discovered that adding an extra constraint on the depth of the tree didn’t make the problem harder. (All variants of the problem he considers are NP-hard, but some are NP-harder than others.) Continue reading →

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