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OptShrink: An algorithm for improved low-rank signal matrix denoising by
  optimal, data-driven singular value shrinkage
v1v2v3v4 (latest)

OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage

25 June 2013
R. Nadakuditi
ArXiv (abs)PDFHTML

Papers citing "OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage"

30 / 30 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
71
4
0
10 Mar 2023
Empirical Bayes PCA in high dimensions
Empirical Bayes PCA in high dimensions
Xinyi Zhong
Chang Su
Z. Fan
108
19
0
21 Dec 2020
ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated
  Noise
ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise
D. Donoho
M. Gavish
Elad Romanov
83
28
0
25 Sep 2020
Tracy-Widom distribution for heterogeneous Gram matrices with
  applications in signal detection
Tracy-Widom distribution for heterogeneous Gram matrices with applications in signal detection
Xiucai Ding
Fan Yang
48
15
0
10 Aug 2020
Optimal singular value shrinkage for operator norm loss
Optimal singular value shrinkage for operator norm loss
W. Leeb
61
11
0
24 May 2020
Detection thresholds in very sparse matrix completion
Detection thresholds in very sparse matrix completion
C. Bordenave
Simon Coste
R. Nadakuditi
91
25
0
12 May 2020
How to reduce dimension with PCA and random projections?
How to reduce dimension with PCA and random projections?
Fan Yang
Sifan Liu
Yan Sun
David P. Woodruff
63
28
0
01 May 2020
Low-rank matrix denoising for count data using unbiased Kullback-Leibler
  risk estimation
Low-rank matrix denoising for count data using unbiased Kullback-Leibler risk estimation
Jérémie Bigot
Charles-Alban Deledalle
51
5
0
28 Jan 2020
Adaptive Structure-constrained Robust Latent Low-Rank Coding for Image
  Recovery
Adaptive Structure-constrained Robust Latent Low-Rank Coding for Image Recovery
Zhao Zhang
Lei Wang
Sheng Li
Yang Wang
Zheng Zhang
Zhengjun Zha
Meng Wang
45
11
0
21 Aug 2019
Spiked separable covariance matrices and principal components
Spiked separable covariance matrices and principal components
Xiucai Ding
Fan Yang
91
57
0
29 May 2019
Rapid evaluation of the spectral signal detection threshold and
  Stieltjes transform
Rapid evaluation of the spectral signal detection threshold and Stieltjes transform
W. Leeb
99
7
0
26 Apr 2019
Time Series Source Separation using Dynamic Mode Decomposition
Time Series Source Separation using Dynamic Mode Decomposition
Arvind Prasadan
R. Nadakuditi
AI4TS
88
6
0
04 Mar 2019
Matrix denoising for weighted loss functions and heterogeneous signals
Matrix denoising for weighted loss functions and heterogeneous signals
W. Leeb
87
25
0
25 Feb 2019
Optimal spectral shrinkage and PCA with heteroscedastic noise
Optimal spectral shrinkage and PCA with heteroscedastic noise
Qiangqiang Wu
Yanjie Liang
89
25
0
06 Nov 2018
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
David Hong
Fan Yang
Jeffrey A. Fessler
Laura Balzano
109
26
0
30 Oct 2018
Heteroskedastic PCA: Algorithm, Optimality, and Applications
Heteroskedastic PCA: Algorithm, Optimality, and Applications
Anru R. Zhang
T. Tony Cai
Yihong Wu
197
72
0
19 Oct 2018
Panoramic Robust PCA for Foreground-Background Separation on Noisy,
  Free-Motion Camera Video
Panoramic Robust PCA for Foreground-Background Separation on Noisy, Free-Motion Camera Video
Brian E. Moore
Chen Gao
R. Nadakuditi
80
38
0
18 Dec 2017
Permutation methods for factor analysis and PCA
Permutation methods for factor analysis and PCA
Yan Sun
82
54
0
02 Oct 2017
Augmented Robust PCA For Foreground-Background Separation on Noisy,
  Moving Camera Video
Augmented Robust PCA For Foreground-Background Separation on Noisy, Moving Camera Video
Chen Gao
Brian E. Moore
R. Nadakuditi
46
10
0
27 Sep 2017
Optimal prediction in the linearly transformed spiked model
Optimal prediction in the linearly transformed spiked model
Edgar Dobriban
W. Leeb
A. Singer
83
20
0
07 Sep 2017
Asymptotic performance of PCA for high-dimensional heteroscedastic data
Asymptotic performance of PCA for high-dimensional heteroscedastic data
David Hong
Laura Balzano
Jeffrey A. Fessler
76
55
0
20 Mar 2017
Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly
  Accelerated Dynamic Imaging
Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging
S. Ravishankar
Brian E. Moore
R. Nadakuditi
Jeffrey A. Fessler
88
71
0
13 Nov 2016
Generalized SURE for optimal shrinkage of singular values in low-rank
  matrix denoising
Generalized SURE for optimal shrinkage of singular values in low-rank matrix denoising
Jérémie Bigot
Charles-Alban Deledalle
D. Féral
67
21
0
24 May 2016
Improved Sparse Low-Rank Matrix Estimation
Improved Sparse Low-Rank Matrix Estimation
Ankit Parekh
I. Selesnick
103
46
0
29 Apr 2016
Enhanced Low-Rank Matrix Approximation
Enhanced Low-Rank Matrix Approximation
Ankit Parekh
I. Selesnick
97
87
0
06 Nov 2015
Testing in high-dimensional spiked models
Testing in high-dimensional spiked models
Iain M. Johnstone
A. Onatski
84
53
0
24 Sep 2015
Joint Covariance Estimation with Mutual Linear Structure
Joint Covariance Estimation with Mutual Linear Structure
I. Soloveychik
A. Wiesel
49
3
0
01 Jul 2015
Weighted Schatten ppp-Norm Minimization for Image Denoising with Local and Nonlocal Regularization
Yuan Xie
97
4
0
07 Jan 2015
Optimal Shrinkage of Singular Values
Optimal Shrinkage of Singular Values
M. Gavish
D. Donoho
155
184
0
29 May 2014
Matrix estimation by Universal Singular Value Thresholding
Matrix estimation by Universal Singular Value Thresholding
S. Chatterjee
491
529
0
06 Dec 2012
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