PulseAugur
EN
LIVE 21:42:07

Math paper details resolvent convergence for sample covariance matrices

This paper investigates the convergence of resolvent matrices for sample covariance matrices with general covariance profiles. The authors establish bounds for the trace of a matrix multiplied by the resolvent, controlled by the Hilbert-Schmidt norm of the matrix. These bounds are dependent on moment conditions of quadratic forms derived from the matrix entries. AI

RANK_REASON This is an academic paper on a mathematical topic related to statistics and machine learning. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Math paper details resolvent convergence for sample covariance matrices

COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Cosme Louart ·

    Resolvent convergence for sample covariance matrices with general covariance profiles and quadratic-form control

    arXiv:2109.02644v4 Announce Type: replace-cross Abstract: We study the resolvent \[ G^z = \left(\frac{1}{n}XX^T - zI_p\right)^{-1}, \qquad z\in\mathbb C,\ \Im(z)>0, \] where $X=(x_1,\ldots,x_n)\in\mathcal M_{p,n}$ is a random matrix with independent, but not necessarily identical…