PhD Seminar: Yifan Sun: "Optimization over structured sparsity"

Friday, November 6, 2020 - 2:40pm to 3:40pm
Zoom - contact for Zoom info.
Event Description: 

Title: Optimization over structured sparsity

Time: 2:40 pm, Friday 11/6

Abstract: As the saying goes, "there are many ways to skin a cat".

While we don't want to go around skinning cats, the world of

optimization is rich with different problems, problem formulations,

and methods and approaches, each with different guarantees and

computational benefits. In this talk we will take a tour down the

problem of structured sparsity in sensing to see how one simple

problem can inspire a wide range of analysis and tools. First, I will

present the optimality conditions for a generalized structured sparse

problem, which can be geometrically visualized as alignment of vectors

and matrices. Then I will introduce three approximation methods for

the problem of phase retrieval, which are a twist on stochastic

gradient and coordinate descent methods. These methods leverage

fundamental numerical linear algebra concepts to give fast approximate

solutions to large-scale problems, which then after postprocessing can

produce more reliable sensing results.

Bio: Yifan Sun received her PhD in Electrical Engineering from the

University of California Los Angeles in 2015, with research focusing

on convex optimization and semidefinite programming. She was then

Technicolor Research and Innovation, focusing on machine learning and

data science applications. More recently, she completed two postdocs,

at the University of British Columbia in Vancouver, Canada and

L’Institut National de Recherche en Informatique et Automatique

(INRIA) in Paris, France.  

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Event Title: 
PhD Seminar: Yifan Sun: "Optimization over structured sparsity"