Machine learning and learning theory research
A couple security researchers claim to have cracked the netflix dataset. The claims of success appear somewhat overstated to me, but the method of attack is valid and could plausibly be substantially improved so as to reveal the movie preferences of a small fraction of Netflix users. The basic idea is to use a heuristic …
… but only the little prize. The BellKor team focused on integrating predictions from many different methods. The base methods consist of: Nearest Neighbor Methods Matrix Factorization Methods (asymmetric and symmetric) Linear Regression on various feature spaces Restricted Boltzman Machines The final predictor was an ensemble (as was reasonable to expect), although it’s a little …
Netflix is running a contest to improve recommender prediction systems. A 10% improvement over their current system yields a $1M prize. Failing that, the best smaller improvement yields a smaller $50K prize. This contest looks quite real, and the $50K prize money is almost certainly achievable with a bit of thought. The contest also comes …
I want to comment on the “Bing copies Google” discussion here, here, and here, because there are data-related issues which the general public may not understand, and some of the framing seems substantially misleading to me. As a not-distant-outsider, let me mention the sources of bias I may have. I work at Yahoo!, which has …
Yahoo! is sponsoring two machine learning events that might interest people. The Key Scientific Challenges program (due March 5) for Machine Learning and Statistics offers $5K (plus bonuses) for graduate students working on a core problem of interest to Y! If you are already working on one of these problems, there is no reason not …