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Talk Abstract
Scaling Up Numerical Machine Learning

Chris Atkeson, Georgia Institute of Technology

Numerical machine learning algorithms attempt to find structure in data. Approaches range from using parametric models such as neural networks to using non-parametric models. This talk will explore the differences between batch learning applications in which a fixed training set is used and continuous learning in which new data is continuously added to the training set.

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1996-1997 Mathematics in High Performance Computing