Workshop on Large Random Matrices and their Applications

(11-13 October 2010 in Télécom-Paris Tech)

**Florent Benaych-George**: Finite rank perturbations of random matrices and free probability theory.**Charles Bordenave**: Heavy-tailed random matrices and the Poisson Weighted Infinite Tree. [slides]**Folkmar Bornemann**: Numerical Evaluation of Distribution Functions for Canonical Matrix Ensembles. [slides]**Djalil Chafaï**: Spectrum of Large Random Markov Chains. [slides]**Romain Couillet**: Deterministic equivalents for unitary Haar matrices. [slides]**Catherine Donati**: Large deviation for the largest eigenvalue of the Hermitian Brownian motion.**Alan Edelman**: A Numerical Linear Algebra View of the Tao-Vu Smallest Singular Value Limit and the SDO extension. [slides(ppt)]**Jakob Hoydis**: Applications of Random Matrices to Small Cell Networks. [slides]**Jean-Paul Ibrahim**: Large deviation properties for some perturbated sample covariance matrices.**Malika Kharouf**: A Central Limit Theorem for Information-Theoretic statistics of Gram random matrices. [slides]**Oleksiy Khorunzhiy**: On sufficient and necessary condition for edge universality in wigner ensemble of random matrices.**Olivier Ledoit**: Eigenvectors of some large sample covariance matrix ensembles. [slides]**Philippe Loubaton**: Exact separation of the eigenvalues of large dimension complex Gaussian Information plus Noise model. [slides]**Mylène Maïda**: Large deviations of extreme eigenvalues of deformed random matrices and performance analysis. [slides]**Camille Mâle**: Norm of Polynomials in Large Random Matrices. [slides]**Boaz Nadler**: Non-parametric Signal Detection and RMT. [slides]**Alain Rouault**: Truncations of Haar unitary matrices and bivariate Brownian bridge. [slides]**Francisco Rubio**: A CLT on the SNR of the diagonally loaded beamformer. [slides]**Øyvind Ryan**: On general criteria for when the spectrum of a combination of random matrices depends only on the spectra of the components. [slides]**Dietrich von Rosen**: High-dimensional analysis and estimation in general multivariate linear models. [slides]**Jack Silverstein**: Estimating Population Eigenvalues From Large Dimensional Sample Covariance Matrices. [slides]**Pascal Vallet**: Eigenspace estimation for source localization using large random matrices. [slides]**Jian-Feng Yao**: On corrections of classical multivariate tests for high-dimensional data}. [slides]**Lu Wei**: On the Demmel condition number distribution with applications in performance analysis of wireless communication systems. [slides]