Fetching the paper…
Reading the bibliography…
We consider the linearly transformed spiked model, where observations $Y_i$ are noisy linear transforms of unobserved signals of interest $X_i$: \begin{align*} Y_i = A_i X_i + \varepsilon_i, \end{align*} for $i=1,\ldots,n$.
Distribution of eigenvalues for some sets of random matrices
V. A. Marchenko and L. A. Pastur · 1967
Earlier work this paper cites.
The reconstruction of structure from electron micrographs of randomly oriented particles
Z. Kam · 1980
Earlier work this paper cites.
Remarks on parallel analysis
A. Buja and N. Eyuboglu · 1992
Earlier work this paper cites.
Probability and Statistical Inference
N. Mukhopadhyay · 2000
Earlier work this paper cites.
On the distribution of the largest eigenvalue in principal components analysis
I. M. Johnstone · 2001
Earlier work this paper cites.
Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
J. Baik, G. Ben Arous, and S. Péché · 2005
Earlier work this paper cites.
Eigenvalues of large sample covariance matrices of spiked population models
J. Baik and J. W. Silverstein · 2006
Earlier work this paper cites.
Digital Signal Processing: Mathematical and Computational Methods, Software Development and Applications
J. M. Blackledge · 2006
Earlier work this paper cites.
On asymptotics of eigenvectors of large sample covariance matrix
Z. Bai, B. Miao, and G. Pan · 2007
Earlier work this paper cites.
Asymptotics of sample eigenstructure for a large dimensional spiked covariance model
D. Paul · 2007
Earlier work this paper cites.
Determining the number of components in a factor model from limited noisy data
S. Kritchman and B. Nadler · 2008
Earlier work this paper cites.
A Wavelet Tour of Signal Processing: The Sparse Way
S. Mallat · 2008
Earlier work this paper cites.
Sample eigenvalue based detection of high-dimensional signals in white noise using relatively few samples
R. R. Nadakuditi and A. Edelman · 2008
Earlier work this paper cites.
Finite sample approximation results for principal component analysis: A matrix perturbation approach
B. Nadler · 2008
Earlier work this paper cites.
Spectral analysis of large dimensional random matrices
Z. Bai and J. W. Silverstein · 2009
Earlier work this paper cites.
Exact matrix completion via convex optimization
E. J. Candès and B. Recht · 2009
Earlier work this paper cites.
An accelerated gradient method for trace norm minimization
S. Ji and J. Ye · 2009
Earlier work this paper cites.
Matrix completion from a few entries
R. H. Keshavan, S. Oh, and A. Montanari · 2009
Earlier work this paper cites.
Variance Components , volume 391
S. R. Searle, G. Casella, and C. E. McCulloch · 2009
Earlier work this paper cites.
Matrix completion with noise
E. J. Candès and Y. Plan · 2010
Earlier work this paper cites.
The power of convex relaxation: Near-optimal matrix completion
E. J. Candès and T. Tao · 2010
Earlier work this paper cites.
Regularization for matrix completion
R. H. Keshavan and A. Montanari · 2010
Earlier work this paper cites.
Matrix completion from a few entries
R. H. Keshavan, A. Montanari, and S. Oh · 2010
Cited alongside, same era.
Collaborative filtering in a non-uniform world: Learning with the weighted trace norm
N. Srebro and R. R. Salakhutdinov · 2010
Cited alongside, same era.
Introduction to the non-asymptotic analysis of random matrices
R. Vershynin · 2010
Cited alongside, same era.
Random Matrix Methods for Wireless Communications
R. Couillet and M. Debbah · 2011
Cited alongside, same era.
Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
V. Koltchinskii, K. Lounici, and A. B. Tsybakov · 2011
Cited alongside, same era.
Estimation of (near) low-rank matrices with noise and high-dimensional scaling
S. Negahban and M. J. Wainwright · 2011
Noisy low-rank matrix completion with general sampling distribution
O. Klopp · 2014
Later among the works it cites.
Optshrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage
R. R. Nadakuditi · 2014
Later among the works it cites.
Signal detection in high dimension: The multispiked case
A. Onatski, M. J. Moreira, and M. Hallin · 2014
Later among the works it cites.
Random matrix theory in statistics: A review
D. Paul and A. Aue · 2014
Later among the works it cites.
Covariance estimation using conjugate gradient for 3D classification in cryo-EM
J. Andén, E. Katsevich, and A. Singer · 2015
Later among the works it cites.
How cryo-EM is revolutionizing structural biology
X.-C. Bai, G. McMullan, and S. H. Scheres · 2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
A simpler approach to matrix completion
B. Recht · 2011
Cited alongside, same era.
Estimation of high-dimensional low-rank matrices
A. Rohde, A. B. Tsybakov, et al · 2011
Cited alongside, same era.
Fourier Analysis: An Introduction , volume 1
E. M. Stein and R. Shakarchi · 2011
Cited alongside, same era.
Estimation of spiked eigenvalues in spiked models
Z. Bai and X. Ding · 2012
Cited alongside, same era.
On sample eigenvalues in a generalized spiked population model
Z. Bai and J. Yao · 2012
Cited alongside, same era.
The singular values and vectors of low rank perturbations of large rectangular random matrices
F. Benaych-Georges and R. R. Nadakuditi · 2012
Cited alongside, same era.
The revolution will not be crystallized
E. Callaway · 2015
Later among the works it cites.
Completing any low-rank matrix, provably
Y. Chen, S. Bhojanapalli, S. Sanghavi, and R. Ward · 2015
Later among the works it cites.
Efficient computation of limit spectra of sample covariance matrices
E. Dobriban · 2015
Later among the works it cites.
High-dimensional asymptotics of prediction: Ridge regression and classification
E. Dobriban and S. Wager · 2015
Later among the works it cites.
A survey on the eigenvalues local behavior of large complex correlated wishart matrices
W. Hachem, A. Hardy, and J. Najim · 2015
Later among the works it cites.
Testing in high-dimensional spiked models
I. M. Johnstone and A. Onatski · 2015
Later among the works it cites.
Covariance matrix estimation for the cryo-EM heterogeneity problem
E. Katsevich, A. Katsevich, and A. Singer · 2015
Later among the works it cites.
Large Sample Covariance Matrices and High-Dimensional Data Analysis
J. Yao, Z. Bai, and S. Zheng · 2015
Later among the works it cites.
Denoising and covariance estimation of single particle cryo-EM images
T. Bhamre, T. Zhang, and A. Singer · 2016
Later among the works it cites.
Blind image deconvolution: theory and applications
P. Campisi and K. Egiazarian · 2016
Later among the works it cites.
Fast steerable principal component analysis
Z. Zhao, Y. Shkolnisky, and A. Singer · 2016
Later among the works it cites.
Algorithms for Single Particle Reconstruction
ASPIRE · 2017
Closest in time.
Factor selection by permutation
E. Dobriban · 2017
Closest in time.
Deterministic parallel analysis
E. Dobriban and A. B. Owen · 2017
Closest in time.
Optimal shrinkage of singular values
M. Gavish and D. L. Donoho · 2017
Closest in time.