This research reveals concentration inequalities in non-linear random matrices, suggesting implications for neural networks and non-commutative polynomials.
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.
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Radosław Adamczak (2025) studied this question.
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