Comments of ikarpov (11)

Comment on post marriage: the gayening:
2009-05-22T08:32:37+00:00
Yeah, +1 for the subject.

Comment on post I'm living in my own private Idaho:
2008-02-22T02:59:36+00:00
where do you play?

Comment on post house-hunting: part 2 of 5000:
2007-11-22T00:22:53+00:00
You should totally buy Kurt's house.

Comment on post epic flying mount!!:
2007-06-20T22:45:23+00:00
It is evidence that the blog search index and main index are somewhat disjoint:

http://blogsearch.google.com/blogsearch?hl=en&q=%22homer+3d%22+%22fermat%27s+last+theorem%22&btnG=Search+Blogs

Comment on post obsession #12358: bsg:
2007-05-14T20:04:30+00:00
Also, parsing is going to be noisy for natural language - that's life. If you want something more reliable but not as deep, just do chunking.

Comment on post obsession #12358: bsg:
2007-05-14T20:03:01+00:00
I'm not sure if it has what you are looking for, but I really enjoyed using NLTK-Lite for NLP stuff. It has taggers, chunkers, parsers, the Brown and the Penn corpora, and other nice stuff.

Comment on post A humbling experience:
2006-08-18T20:58:29+00:00
Keep in mind that computers and people play the game very differently, so you might also through in a couple live opponents in occasionally.

Comment on post perhaps perhaps perhaps:
2006-03-26T11:28:16+00:00
I trust you have seen this

Comment on post perhaps perhaps perhaps:
2006-03-26T11:25:24+00:00
When I hear the phrase "Company X is Chip Manufacturer Y powered", I think of water boilers and steam turbines seating on top of a nice array of overheating pentiums.

Comment on post busy week, fun weekend:
2005-08-23T22:16:23+00:00
Ooops that link is actually http://www.cs.utexas.edu/users/dsb/cs387h/DBI2005-Group5-Streams.pdf

Comment on post busy week, fun weekend:
2005-08-23T22:14:06+00:00
Classifying, indexing and clustering music has been an interest of mine for some time now. I tried a hidden markov model, self-organizing maps, and a few more esoteric NN architectures. In general, what you are looking for is papers on "query by humming". I would be curious to see if you can get an efficient implementation of it using one of the streaming database systems, perhaps using dynamic time warping distance-based indecies. We dug up some references for this during a class presentation last semester for a database implementation course. Eamonn Keogh is a good guy to look at for time series clustering and indexing research.

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