CSE-280: SUM-OF-SQUARES (SoS) & GAUSSIAN PROCESSES

This will be a one-quarter (Winter-2024) seminar course discussing a recent result I by Jonathan Shi and myself. The main contribution of this result is that it introduces a new SoS hierarchy to certify the values of the expected supremum of Gaussian process, to some (constant) threshold of approximability. The threshold is widely-believed to be optimal among polynomial-time algorithms. The paper also makes a conjecture about the optimality of this hierarchy for a broad class of Gaussian processes, providing examples of modified Gaussian processes where the HES hierarchy provably outperforms local-iterative algorithms such as Hessian ascent (or provides strong evidence of doing so). Proving (or disproving) this conjecture would unravel interesting connections between high-dimensional probability, sum-of-squares, random matrices and free probability.

Meeting Time: Tuesdays, 11:40 AM - 1:40 PM PST.

Location: Social Sciences Building 2, Room 137. (Meetings will be zoomed; Contact me for the link and/or access to the recordings).

Lectures: Video recordings

SYLLABUS

NOTES & RESOURCES

I have some offline notes in my (poor) hand-writing that were shared with the students. For a list of relevant papers and monographs that are relevant, contact me.