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I recently completed my PhD (Dec. 08) on large-scale Machine Learning.
Dissertation title: Multi-Tree Monte Carlo Methods for Fast, Scalable Machine Learning
My dissertation work focused on fast/scalable methods for massive datasets using Monte Carlo
principles. For instance, we have fast Monte Carlo versions of the SVD and most kernel estimators (kernel density estimation, etc.). Our methods take only seconds or minutes to perform complex learning computations that would normally take years or decades. This enables the use of sophisticated learning algorithms on massive datasets.
Other work has included prediction in time series and dynamical systems, the Netflix prize competition (collaborative
filtering), and hidden state discovery.
I was advised by Charles Isbell, and co-advised by Alex Gray.
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