Random matrix theory and high-dimensional statistics

July 10-30,  2011,   Changchun,   China

The Summer School, Random matrix theory and its applications to high-dimensional statistics, is one of two summer schools founded jointly by the CNRS of France and the NSF of China each year in the domain of mathematics.

The main theme of the program is the probability theory of random matrices in general and their applications in mathematical statistics, wireless communication, random networks and more generally in stochastic modeling. The following topics (among others) will be covered:

Convergence of spectral measures of random matrices; universality; Large deviation theory for matrix ensembles; Central limit theorems for linear functional of spectral measures; Spiked population models, deformed matrix models; Free probability theory.

Limiting distributions of general sample covariance matrices and F-matrices; Estimation of the population spectral measure from sample covariance matrices; Testing and estimation in presence of high-dimensional data; Applications for signal detection; capacity analysis of telecommunication networks and analysis of time series.


List of the participants is here (as of August 8, 2011):