Title	Rank-one matrix estimation and Hamilton-Jacobi equations - 2
Creator	Mourrat, Jean Christophe
Publisher	Banff International Research Station for Mathematical Innovation and Discovery
Date Issued	2020-05-19T10:00
Description	We consider the problem of estimating a large rank-one matrix, given noisy observations. This inference problem is known to have a phase transition, in the sense that the 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 to obtain better rates of convergence, and also seems more amenable to extensions to other models such as spin glasses.
Extent	72.0 minutes
Subject	Mathematics; Probability Theory
Type	Moving Image
File Format	video/mp4
Language	eng
Notes	Author affiliation: New York University
Series	BIRS Workshop Lecture Videos (Banff, Alta)
Date Available	2020-11-16
Provider	Vancouver : University of British Columbia Library
Rights	Attribution-NonCommercial-NoDerivatives 4.0 International
DOI	10.14288/1.0394954
URI	http://hdl.handle.net/2429/76502
Affiliation	Non UBC
Peer Review Status	Unreviewed
Scholarly Level	Researcher
Rights URI	http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository	DSpace

Open Collections

BIRS Workshop Lecture Videos