Recover the spectrum of covariance matrix: a non-asymptotic iterative method

2022/01/01 by Juntao Duan, Duan, Juntao, Popescu, Ionel +2
Computer Science · Engineering · Mathematics · #Blind Source Separation Techniques #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Random Matrices and Applications #Sparse and Compressive Sensing Techniques

paper · pdf · doi:10.48550/arxiv.2201.00230

openalex publication_date 2022/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

It is well known the sample covariance has a consistent bias in the spectrum, for example spectrum of Wishart matrix follows the Marchenko-Pastur law. We in this work introduce an iterative algorithm 'Concent' that actively eliminate this bias and recover the true spectrum for small and moderate dimensions.

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