Yale Daily News, continued

I pointed to this article in the Yale Daily News about computer science when it came out in April.  Giorgos just pointed me back to it again, and I'd have to say, it's worth looking at again for the comments, which I'm still trying to grok.   

MMDS

I'm hanging out at MMDS -- the Workshop on Algorithms for Modern Massive Datasets at Stanford.  The crowd is surprisingly huge, with a greater number of people in "adjacent" areas (math/statistics/machine learning) and industry than is normal for me.   It's very exciting to see such wide-scale interest.

Right now, though, the non-theorists are having to listen to a very theoretical session:

11:00 - 11:30 Ping Li Probabilistic Hashing for Efficient Search and Learning on Massive Data 11:30 - 12:00 Ashish Goel Real Time Social Search and Related Problems 12:00 - 12:30 Andrew Goldberg Hub Labels in Databases: Shortest Paths for the Masses

Fun stuff!

I just enjoyed an interesting aspect of Ashish's talk.  He was putting the social search problem in a framework where you first do preprocessing on the social graph (using distance oracles for shortest paths), and then do incremental updates (corresponding to when someone say does a new Tweet, you update the keywords associated with that user).  I like it because I talk about the preprocessing + query answering approach (using examples like suffix trees, least common ancestor data structures) in my undergrad class.  This preprocessing + incremental update + query answering example in the context of social search would make a nice addition (that students can hopefully appreciate), if I could simplify it in a reasonable way.

On NPR (Morning Edition)

Groupon is being discussed on NPR (Morning Edition), which means we get a phone call again.  Our graphs are reproduced on the site, and John Byers speaks for us (Giorgos and me with John).