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Universality of approximate message passing algorithms

Wednesday, June 24, 2020 - 12:00pm

***  Joint with Applied Mathematics Seminar  ***

Speaker:   Wei-Kuo Chen, University of Minnesota

Abstract:   Approximate Message Passing (AMP) algorithms are non-linear power iterations originally arising from the context of compressed sensing. In this talk, I will introduce a Lipschitzian functional iteration, as a generalization of the AMP algorithms, and discuss its universality in disorder. In addition, I will explain how our results imply universality in a number of AMPs popularly adapted in Bayesian inferences and optimizations in spin glasses.

This is based on a joint work with Wai-Kit Lam.