|Date: Monday, February 19, 2018
Location: 1866 East Hall (4:00 PM to 5:00 PM)
Title: Non-asymptotic spectral properties of the heavy-tailed random matrices
Abstract: The non-asymptotic branch of Random Matrix Theory is concerned to get explicit high probability estimates for the large enough, but fixed size matrices (usually in trade of precise constants). This goal naturally brings into play some beautiful methods of high-dimensional probability and geometry, such as concentration of measure phenomenon. I will introduce some ideas and results of the theory, talking about the spectral properties of heavy-tailed random matrices (i.e. with the entries distributions decaying asymptotically slower than gaussian).
Speaker: Elizaveta Rebrova
Institution: University of Michigan
Event Organizer: Guilherme Silva firstname.lastname@example.org