Posted by Cheng Soon Ong on May 17, 2011
After the success of the Netflix prize, it seems that overstock.com would also like to entice smart machine learners to solve their recommendation problem too. The idea is the same, improve 10% over the baseline to win 1 million dollars.
Details are available at: http://overstockreclabprize.com/
A couple of things are different though:
- There is a 250,000 bonus for your academic institution.
- The leaders of the Netflix prize were all using ensemble type classifiers (see literature below, and previous post), and it seems like the reclab prize wants to have some diversity by actually having "peer review" to choose the semi-finalists.
- Instead of having a fixed training and test set, the best algorithms would be run against live traffic.
- Since software is much smaller than the data, it makes much more sense to move source code to data than vice versa. And competitors must submit source only!
- You can (kind of) use third party code, as long as it is on Maven. Strange restriction on the type license really. It may make sense to not allow GPL "contamination", but all the other open source licenses?
You can bias the competition to your favour by nominating your friends as reviewers. ;-)
The Netflix winners
- Y. Koren, "The BellKor Solution to the Netflix Grand Prize" PDF (2009).
- A. Töscher, M. Jahrer, R. Bell, "The BigChaos Solution to the Netflix Grand Prize" PDF (2009).
- M. Piotte, M. Chabbert, "The Pragmatic Theory solution to the Netflix Grand Prize" PDF (2009).
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