The weekly SILO Seminar Series is made possible through the generous support of the 3M Company and its Advanced Technology Group


with additional support from the Analytics Group of the Northwestern Mutual Life Insurance Company

Northwestern Mutual

A geometric analysis of algorithms for phase retrieval and other single-index models with even link functions

Yan Shuo Tan,

Date and Time: Nov 22, 2017 (12:30 PM)
Location: Orchard room (3280) at the Wisconsin Institute for Discovery Building


Mathematical phase retrieval is the problem of solving systems of quadratic equations. In the first half of this talk, I will discuss recent approaches to this problem, focusing on stochastic gradient methods. In the second half, I will discuss how these algorithms can be extended and generalized. The first extension is to make use of sparsity constraints on the signal vector; the second is to address model ambiguity. In this respect, it is helpful to think of the phase retrieval model as a single-index model with a quadratic link function. In real life applications, it is possible to have link functions that are not exactly quadratic. Possibly, these link functions are also unknown to the observer. I will discuss what can be done to handle such situations.

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