UBC Probability Seminar: Jean-Christoph Mourrat (Online)
Topic
Rank-one matrix estimation and Hamilton-Jacobi equations II
Speakers
Details
We consider the problem of estimating large rank-one matrix, given noisy observations. This inference problem is known to have a phase transition, in the sense that partial recovery of the original matrix is only possible if the signal-to-noise ratio exceeds a (non-zero) value. We will present a new proof of this fact based on the study of a Hamilton-Jacobi equation. This alternative argument allows one to obtain better rates of convergence, and also seems more amenable to extensions to other models such as spin glasses.
Additional Information
Please contact organizers for meeting ID at mathav@math.ubc.ca
Jean-Christoph Mourrat, NYU
Jean-Christoph Mourrat, NYU
This is a Past Event
Event Type
Scientific, Seminar
Date
May 20, 2020
Time
-
Location