Concentration of measure for non-linear random matrices with applications to neural networks and non-commutative polynomials

math.PR arXiv:2507.07625
View PDF arXiv JSON

Abstract

We prove concentration inequalities for several models of non-linear random matrices. As corollaries we obtain estimates for linear spectral statistics of the conjugate kernel of neural networks and non-commutative polynomials in (possibly dependent) random matrices.

PDF Viewer