Matrix Concentration and Synthetic Data

Job Candidate Talk
Thursday, March 10, 2022 - 11:00am for 1 hour (actually 50 minutes)
March Boedihardjo – UC Irvine – marchb@uci.edu
Christian Houdré

Classical matrix concentration inequalities are sharp up to a logarithmic factor. This logarithmic factor is necessary in the commutative case but unnecessary in many classical noncommutative cases. We will present some matrix concentration results that are sharp in many cases, where we overcome this logarithmic factor by using an easily computable quantity that captures noncommutativity. Joint work with Afonso Bandeira and Ramon van Handel.

Due to privacy, access to real data is often restricted. Data that are not completely real but resemble certain properties of real data become natural substitutes. Data of this type are called synthetic data. I will talk about the extent to which synthetic data may resemble real data under privacy and computational complexity restrictions. Joint work with Thomas Strohmer and Roman Vershynin.

The link to the online talk: