Logo

Mathematical Sciences Research Institute

Home » Workshop » Schedules »  Principle Components of Spiked Covariance Matrices

Principle Components of Spiked Covariance Matrices

[HYBRID WORKSHOP] Connections and Introductory Workshop: Universality and Integrability in Random Matrix Theory and Interacting Particle Systems, Part 2 September 20, 2021 - September 24, 2021

September 21, 2021 (04:00 PM PDT - 04:50 PM PDT)
Speaker(s): Ke Wang (Hong Kong University of Science and Technology)
Location: MSRI: Simons Auditorium, Online/Virtual
Primary Mathematics Subject Classification No Primary AMS MSC
Secondary Mathematics Subject Classification No Secondary AMS MSC
Video
No Video Uploaded
Abstract

Computing the eigenvalues and eigenvectors of a large matrix is a basic task in high dimensional data analysis with many applications in computer science and statistics. In practice, however, data is often perturbed by noise. In this talk, we will focus on the spiked covariance matrix model, a popular and sophisticated model proposed by Johnstone. We will present some recent results on the limiting behavior of the extreme eigenvalues and eigenvectors of the spiked covariance matrices in the supercritical case. This talk is based on joint work with Zhigang Bao, Xiucai Ding, and Jingming Wang.

Supplements No Notes/Supplements Uploaded
Video/Audio Files
No Video Files Uploaded