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De-biased sparse PCA: Inference and testing for eigenstructure of large
  covariance matrices

De-biased sparse PCA: Inference and testing for eigenstructure of large covariance matrices

31 January 2018
Jana Janková
Sara van de Geer
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Papers citing "De-biased sparse PCA: Inference and testing for eigenstructure of large covariance matrices"

3 / 3 papers shown
Title
On Support Recovery with Sparse CCA: Information Theoretic and
  Computational Limits
On Support Recovery with Sparse CCA: Information Theoretic and Computational Limits
Nilanjana Laha
Rajarshi Mukherjee
40
4
0
14 Aug 2021
Uncertainty quantification for nonconvex tensor completion: Confidence
  intervals, heteroscedasticity and optimality
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
Changxiao Cai
H. Vincent Poor
Yuxin Chen
20
23
0
15 Jun 2020
Singular vector and singular subspace distribution for the matrix
  denoising model
Singular vector and singular subspace distribution for the matrix denoising model
Z. Bao
Xiucai Ding
Ke Wang
21
51
0
27 Sep 2018
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