Mathematics Colloquia and Seminars

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Description

In this talk, I will present some recent results on the analysis of the first-order behavior (convergent limits) and second-order behavior (asymptotic distributions) of eigenvectors of large random matrices. I will review these results using the classical model of large sample covariance matrices as a guiding example. I will also discuss related results for other important classes of large random matrices arising in modern statistics and deep learning, including kernel random matrices, random geometric graphs, and products of random matrices.