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Speaker: Ming Yuan (Columbia)

Title: Spectral Learning for High Dimensional Tensors

Abstract: Matrix perturbation bounds developed by Weyl, Davis, Kahan and Wedin and others play a central role in many statistical and machine learning problems. I shall discuss some of the recent progresses in developing similar bounds for higher order tensors. I will highlight the intriguing differences from matrices, and explore their implications in spectral learning problems.

seminars/stat/sep222022.txt · Last modified: 2022/09/08 09:53 by rakhi