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

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

27 May 2021
Joshua Agterberg
Zachary Lubberts
Carey Priebe
ArXivPDFHTML

Papers citing "Entrywise Estimation of Singular Vectors of Low-Rank Matrices with Heteroskedasticity and Dependence"

7 / 7 papers shown
Title
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in
  heteroskedastic PCA
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA
Yuchen Zhou
Yuxin Chen
40
4
0
10 Mar 2023
Exact Minimax Optimality of Spectral Methods in Phase Synchronization
  and Orthogonal Group Synchronization
Exact Minimax Optimality of Spectral Methods in Phase Synchronization and Orthogonal Group Synchronization
An Zhang
42
5
0
12 Sep 2022
Bayesian Sparse Gaussian Mixture Model in High Dimensions
Bayesian Sparse Gaussian Mixture Model in High Dimensions
Dapeng Yao
Fangzheng Xie
Yanxun Xu
33
1
0
21 Jul 2022
Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms
Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms
Joshua Agterberg
Jeremias Sulam
21
0
0
08 Feb 2022
Bias-adjusted spectral clustering in multi-layer stochastic block models
Bias-adjusted spectral clustering in multi-layer stochastic block models
Jing Lei
K. Lin
35
47
0
18 Mar 2020
Signal-plus-noise matrix models: eigenvector deviations and fluctuations
Signal-plus-noise matrix models: eigenvector deviations and fluctuations
Joshua Cape
M. Tang
Carey E. Priebe
33
48
0
01 Feb 2018
Sparse Principal Component Analysis with missing observations
Sparse Principal Component Analysis with missing observations
Karim Lounici
63
43
0
31 May 2012
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