Entrywise Estimation of Singular Vectors of Low-Rank Matrices With Heteroskedasticity and Dependence

DOI10.1109/TIT.2022.3159085zbMath1505.62495arXiv2105.13346OpenAlexW3165011705WikidataQ114084322 ScholiaQ114084322MaRDI QIDQ5088580

Joshua S. Agterberg, Zachary Lubberts, Carey E. Priebe

Publication date: 13 July 2022

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2105.13346

zbMATH Keywords

singular vectorsestimatorhigh-dimensional low-rank matrices corrupted by additive subgaussian noise

Mathematics Subject Classification ID

Non-Markovian processes: estimation (62M09)

Related Items (2)

Euclidean Representation of Low-Rank Matrices and Its Geometric Properties ⋮ Entrywise limit theorems for eigenvectors of signal-plus-noise matrix models with weak signals

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