Every "best paper" from Computer Science conferences since 1996
jeffhuang.com
jeffhuang.com
Lifshits is a research scientist at Y!R.
I wonder what long-term effects this will have on the computer field and on computer science research at universities.
Regarding "buying brains", being at Y!R is a great experience for me and it matches all the perks of being in academia (you can publish almost anything, work with students, teach at universities if you want, etc).
For a starter, this is a very small subset of computer science conferences (e.g., the main software engineering and programming language conferences are missing). I'm not sure in which field Yahoo! Research works (looks like data mining), but in SE and PL, they are inexistent.
Best paper awards are just one metric among many. Citations, venue impact factor, number of publications are other (imperfect) metrics. It's probably fair to say that MIT and other big universities and corporate labs (IBM and Microsoft) have high scores in all of these metrics, whereas Yahoo! Research is still too young and too small to compete with even smaller but dynamic universities w.r.t. these metrics.
I go through 2-10 papers a day, nearly on PL research, semantics, type-theory and implementation lore. There are a bunch of us on HN, some I correspond with via email, others twitter.
EDIT: 2-10 papers a day is an awesome rate!
There is a huge community of PL enthusiasts.
We can setup a site, but the field is too diverse. Right now it mostly makes sense as each of use tweeting a summary of a paper :-)
Email's in my profile.
Hi there partition,
I can't just send papers your way, but you're free to ask me questions and I will relay to my social circle of PL snobs (most of whom are in my twitter follows anyway)
I rarely read the abstracts. I find interesting papers in the references of other interesting papers.
I usually skip the first 15% of the introductory prose, go to the meat, jump to the conclusions and "future work", and if I think the paper covers enough ground, I fast forward to its references and see if the authors are aware of the seminal works. Only then do I actually read it.
For the truly important ones, you're already aware for their findings from texts, since they're cited often. For the useless ones (the majority) you're just interested in one idea, technique, finding or implementation method, and it's easy to zoom in. But from time to time you will come across a diamond in the rough that isn't as well known as it should.
That said, some more publications/insight on those systems would be nice to see.
A google search of the site is sometimes more productive. For instance:
If I can't find a paper through citesser, I usually just do a regular google search, and often find the paper elsewhere on the web. Google scholar is pretty much my last resort, and I really haven't had much luck finding freely downloadable papers through it.
in terms of metrics of research quality, not all conferences are equal, and "best" papers are often selected by a relatively small group of people whose decision isn't really validated too much.
I guess it's the old truism of not being able to prove something does not exist
http://www-ai.ijs.si/SasoDzeroski/ICML99/award.html via http://www.machinelearning.org/icml.html
in machine learning, i think the significant conferences are NIPS (http://www.nips.cc/), ICML, UAI (e.g., http://event.cwi.nl/uai2010/), and AISTATS (http://www.aistats.org/).