Machine learning and learning theory research
The NYAS ML symposium grew again this year to 170 participants, despite the need to outsmart or otherwise tunnel through a crowd. Perhaps the most distinct talk was by Bob Bell on various aspects of the Netflix prize competition. I also enjoyed several student posters including Matt Hoffman‘s cool examples of blind source separation for …
I attended KDD this year. The conference has always had a strong grounding in what works based on the KDDcup, but it has developed a halo of workshops on various subjects. It seems that KDD has become a place where the economy meets machine learning in a stronger sense than many other conferences. There were …
Carla Vicens and Eric Siegel contacted me about Predictive Analytics World in San Francisco February 18&19, which I wasn’t familiar with. A quick look at the agenda reveals several people I know working on applications of machine learning in businesses, covering deployed applications topics. It’s interesting to see a business-focused machine learning conference, as it …
This post is about a technology which could develop in the future. Right now, a new drug might be tested by finding patients with some diagnosis and giving or not giving them a drug according to a secret randomization. The outcome is observed, and if the average outcome for those treated is measurably better than …
Apparently, the company Spock is setting up a $50k entity resolution challenge. $50k is much less than the Netflix challenge, but it’s effectively the same as Netflix until someone reaches 10%. It’s also nice that the Spock challenge has a short duration. The (visible) test set is of size 25k and the training set has …