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SUMMARY:AMS Weekly Seminar w/ Tyrus Berry (George Mason University) @ Krieger 205 or Zoom
DESCRIPTION:Title: Beyond Regression: Operators and Extrapolation in Machine Learning \nAbstract: In this talk we first suggest a unification of regression-based machine learning methods\, including kernel regression and various types of neural networks. We then consider the limitations of such methods\, especially the curse-of-dimensionality\, and the various potential solutions that have been proposed including: (1) Barron’s existence result\, (2) leveraging regularity\, and (3) assuming special structure in the data such as independence or redundancy. Finally\, we consider operator-learning and extrapolation as emerging directions for machine learning. Operator-learning is the more developed of the two\, and we show how learning operators allows intrinsic regularization\, uncertainty quantification\, and can represent many-to-one and one-to-many mappings. However\, extrapolation remains the final frontier in machine learning\, and we discuss an emerging approach and the mathematics that may underly it. \nHere is the zoom link is: https://wse.zoom.us/j/95448608570
URL:https://engineering.jhu.edu/ams/event/ams-weekly-seminar-w-tyrus-berry-george-mason-university-maryland-110-or-zoom/
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