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0901.3245
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Finite sample approximation results for principal component analysis: a matrix perturbation approach
21 January 2009
B. Nadler
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Papers citing
"Finite sample approximation results for principal component analysis: a matrix perturbation approach"
50 / 116 papers shown
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Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
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B. Nadler
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Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
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Marco Mondelli
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Estimators for multivariate allometric regression model
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17 Feb 2024
High-Dimensional Canonical Correlation Analysis
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V. Gorin
351
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28 Jun 2023
Dynamic User Segmentation and Usage Profiling
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211
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27 May 2023
On the Multiway Principal Component Analysis
Jialin Ouyang
Ming Yuan
319
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14 Feb 2023
Support Recovery in Sparse PCA with Non-Random Missing Data
Hanbyul Lee
Qifan Song
Jean Honorio
242
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03 Feb 2023
Resampling Sensitivity of High-Dimensional PCA
Haoyu Wang
275
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30 Dec 2022
Theoretical Guarantees for Sparse Principal Component Analysis based on the Elastic Net
Teng Zhang
Haoyi Yang
Lingzhou Xue
CML
363
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29 Dec 2022
A CLT for the LSS of large dimensional sample covariance matrices with diverging spikes
Annals of Statistics (Ann. Stat.), 2022
Zhijun Liu
Jiang Hu
Z. Bai
Haiyan Song
557
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12 Dec 2022
A note on the prediction error of principal component regression in high dimensions
Theory of Probability and Mathematical Statistics (TPMS), 2022
L. Hucker
Martin Wahl
298
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09 Dec 2022
SIMPLE-RC: Group Network Inference with Non-Sharp Nulls and Weak Signals
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Yingying Fan
Jinchi Lv
Fan Yang
359
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31 Oct 2022
Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks
Shyam Venkatasubramanian
S. Gogineni
Bosung Kang
Ali Pezeshki
M. Rangaswamy
Vahid Tarokh
308
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07 Sep 2022
Meta Sparse Principal Component Analysis
Imon Banerjee
Jean Honorio
333
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18 Aug 2022
Support Recovery in Sparse PCA with Incomplete Data
Neural Information Processing Systems (NeurIPS), 2022
Hanbyul Lee
Qifan Song
Jean Honorio
263
3
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30 May 2022
A CLT for the LSS of large dimensional sample covariance matrices with unbounded dispersions
Zhijun Liu
Jiang Hu
Z. Bai
Haiyan Song
167
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15 May 2022
Capturing the Denoising Effect of PCA via Compression Ratio
Neural Information Processing Systems (NeurIPS), 2022
Chandra Sekhar Mukherjee
Nikhil Doerkar
Jiapeng Zhang
216
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22 Apr 2022
Generative Principal Component Analysis
International Conference on Learning Representations (ICLR), 2022
Zhaoqiang Liu
Jiulong Liu
Subhro Ghosh
Jun Han
Jonathan Scarlett
272
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18 Mar 2022
The limiting spectral distribution of large dimensional general information-plus-noise type matrices
Journal of theoretical probability (J. Theor. Probab.), 2022
Huanchao Zhou
Z. Bai
Jiang Hu
186
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28 Jan 2022
Inference for Heteroskedastic PCA with Missing Data
Annals of Statistics (Ann. Stat.), 2021
Yuling Yan
Yuxin Chen
Jianqing Fan
417
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26 Jul 2021
Feature Grouping and Sparse Principal Component Analysis with Truncated Regularization
Haiyan Jiang
Shanshan Qin
Oscar Hernan Madrid Padilla
403
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25 Jun 2021
Biwhitening Reveals the Rank of a Count Matrix
SIAM Journal on Mathematics of Data Science (SIMODS), 2021
Boris Landa
Thomas T. Zhang
Y. Kluger
413
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25 Mar 2021
Empirical Bayes PCA in high dimensions
Xinyi Zhong
Chang Su
Z. Fan
598
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21 Dec 2020
Spectral Methods for Data Science: A Statistical Perspective
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Yuejie Chi
Jianqing Fan
Cong Ma
696
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15 Dec 2020
Optimal High-order Tensor SVD via Tensor-Train Orthogonal Iteration
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Yuchen Zhou
Anru R. Zhang
Lili Zheng
Yazhen Wang
446
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06 Oct 2020
ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise
Annals of Statistics (Ann. Stat.), 2020
D. Donoho
M. Gavish
Elad Romanov
414
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25 Sep 2020
Edge statistics of large dimensional deformed rectangular matrices
Journal of Multivariate Analysis (JMA), 2020
Xiucai Ding
Fan Yang
422
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01 Sep 2020
Statistical inference for principal components of spiked covariance matrices
Annals of Statistics (Ann. Stat.), 2020
Z. Bao
Xiucai Ding
Jingming Wang
Ke Wang
484
53
0
27 Aug 2020
An
ℓ
p
\ell_p
ℓ
p
theory of PCA and spectral clustering
Emmanuel Abbe
Jianqing Fan
Kaizheng Wang
397
6
0
24 Jun 2020
Fast Robust Subspace Tracking via PCA in Sparse Data-Dependent Noise
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2020
Praneeth Narayanamurthy
Namrata Vaswani
500
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14 Jun 2020
Non-Sparse PCA in High Dimensions via Cone Projected Power Iteration
Yufei Yi
Matey Neykov
234
2
0
15 May 2020
Lower bounds for invariant statistical models with applications to principal component analysis
Martin Wahl
214
6
0
14 May 2020
On the Distribution of an Arbitrary Subset of the Eigenvalues for some Finite Dimensional Random Matrices
Random Matrices. Theory and Applications (RMTA), 2019
M. Chiani
A. Zanella
272
1
0
02 Jan 2020
The limits of the sample spiked eigenvalues for a high-dimensional generalized Fisher matrix and its applications
Dandan Jiang
Jiang Hu
Zhiqiang Hou
148
8
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06 Dec 2019
Adversarially Robust Low Dimensional Representations
Annual Conference Computational Learning Theory (COLT), 2019
Pranjal Awasthi
Vaggos Chatziafratis
Xue Chen
Aravindan Vijayaraghavan
AAML
OOD
405
12
0
29 Nov 2019
Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon
Bernoulli (Bernoulli), 2019
A. Lodhia
Keith D. Levin
Elizaveta Levina
200
3
0
16 Oct 2019
A greedy anytime algorithm for sparse PCA
Annual Conference Computational Learning Theory (COLT), 2019
Guy Holtzman
Adam Soffer
Dan Vilenchik
389
16
0
15 Oct 2019
Subspace Estimation from Unbalanced and Incomplete Data Matrices:
ℓ
2
,
∞
\ell_{2,\infty}
ℓ
2
,
∞
Statistical Guarantees
Changxiao Cai
Gen Li
Yuejie Chi
H. Vincent Poor
Yuxin Chen
514
13
0
09 Oct 2019
Subexponential-Time Algorithms for Sparse PCA
Foundations of Computational Mathematics (FoCM), 2019
Yunzi Ding
Dmitriy Kunisky
Alexander S. Wein
Afonso S. Bandeira
627
75
0
26 Jul 2019
Uniform bounds for invariant subspace perturbations
SIAM Journal on Matrix Analysis and Applications (SIMAX), 2019
Anil Damle
Yuekai Sun
298
22
0
20 May 2019
Low-Rank Principal Eigenmatrix Analysis
Krishnakumar Balasubramanian
Elynn Y. Chen
Jianqing Fan
Xiang Wu
318
0
0
28 Apr 2019
Generalized Four Moment Theorem with an application to the CLT for the spiked eigenvalues of high-dimensional general Fisher-matrices
Dandan Jiang
Zhiqiang Hou
Z. Bai
204
1
0
11 Apr 2019
An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA
Shixiang Chen
Shiqian Ma
Lingzhou Xue
H. Zou
266
14
0
27 Mar 2019
Principal components in linear mixed models with general bulk
Z. Fan
Yi Sun
Zhichao Wang
303
9
0
22 Mar 2019
Stochastic Linear Bandits with Hidden Low Rank Structure
Sahin Lale
Kamyar Azizzadenesheli
Anima Anandkumar
B. Hassibi
287
30
0
28 Jan 2019
Large dimensional analysis of general margin based classification methods
Hanwen Huang
Qinglong Yang
439
9
0
23 Jan 2019
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
David Hong
Fan Yang
Jeffrey A. Fessler
Laura Balzano
389
36
0
30 Oct 2018
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