On estimation of the noise variance in high-dimensional probabilistic
principal component analysis

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On estimation of the noise variance in high-dimensional probabilistic principal component analysis

18 August 2013

Damien Passemier

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Papers citing "On estimation of the noise variance in high-dimensional probabilistic principal component analysis"

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Title
The Role of Hyperparameters in Predictive Multiplicity Mustafa Cavus Katarzyna Wo'znica Przemysław Biecek 80 0 0 13 Mar 2025
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 144 20 0 10 Jan 2021
Sparse Equisigned PCA: Algorithms and Performance Bounds in the Noisy Rank-1 Setting Arvind Prasadan R. Nadakuditi D. Paul 59 0 0 22 May 2019
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data David Hong Fan Yang Jeffrey A. Fessler Laura Balzano 105 26 0 30 Oct 2018
Wald Statistics in high-dimensional PCA Matthias Loffler 40 1 0 10 May 2018
Exact Dimensionality Selection for Bayesian PCA C. Bouveyron Pierre Latouche Pierre-Alexandre Mattei 30 17 0 08 Mar 2017
Hypergeometric Functions of Matrix Arguments and Linear Statistics of Multi-Spiked Hermitian Matrix Models Damien Passemier M. Mckay Yang Chen 107 6 0 03 Jun 2014
Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrix Models Damien Passemier M. Mckay Yang Chen 103 12 0 26 Feb 2014
Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model D. Donoho M. Gavish Iain M. Johnstone 172 208 0 04 Nov 2013