This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 211
Type: Invited
Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract - #306244
Title: Statisticians: 3, Computer Scientists: 35
Author(s): David Purdy*+
Companies: University of California, Berkeley
Address: 180 Brannan, #319, San Francisco, CA, 94107,
Keywords: Machine Learning ; Future of statistics ; Ensemble methods ; Sparse data

John Tukey and Leo Breiman warned us that a day would come when statistics would need to focus more on computing, or risk losing good students to computer science. The Netflix Prize provides many examples of how our field needs to do more.

In the top 2 teams, participants with a computer science background vastly outnumbered those with a statistics background. There are a number of lessons that the field of statistics can learn from the fact that undergraduates in CS were well equipped to compete, while statisticians at all levels were not well prepared to implement advanced algorithms.

In this talk, I will address methodological issues arising with such a large, sparse dataset, how it demands serious computational talents, and where there is ample room for statistics to make contributions.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

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