Hyperbolic Relaxations of Locally Positive Semidefinite Matrices

Series
ACO Student Seminar
Time
Friday, October 9, 2020 - 1:00pm for 1 hour (actually 50 minutes)
Location
https://bluejeans.com/264244877/0166
Speaker
Kevin Shu – Math, Georgia Tech – kshu8@gatech.eduhttps://math.gatech.edu/people/kevin-shu
Organizer
He Guo

Semidefinite programming is a powerful optimization tool, which involves optimizing linear functions on a slice of the positive semidefinite matrices. Locally PSD matrices are a natural relaxation of the PSD matrices which can be useful in reducing the space required for semidefinite optimization. We use the theory of hyperbolic polynomials to give precise quantitative bounds on the quality of the approximation resulting from optimizing over the locally-psd cone instead of the PSD cone.