April 30, 2004: Distinguished Lecturer Seminar, Speaker Robert Schapire
Speaker: Robert Schapire (Princeton University)
Title: Modern Approaches to Machine Learning

Date: Friday April 30, 2004
Time: 11:00 AM
Location: Room 1000 SEO

This talk will focus on a general-purpose machine-learning method called boosting. The main idea of this method is to produce a very accurate classification rule by combining rough and moderately inaccurate ?rules of thumb?. While rooted in a theoretical framework of machine learning, boosting has been found to perform quite well empirically. In this talk, I will introduce the boosting algorithm AdaBoost, and explain the underlying theory of boosting, including our explanation of why boosting often does not suffer from overfitting, as well as some of the myriad other theoretical points of view that have been taken on this single algorithm. I also will describe some recent applications of boosting.

Host: Professor Bob Sloan

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