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Raj Rao Nadakuditi
Raj Rao Nadakuditi
Associate Professor, University of Michigan
在 umich.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Random matrix theory
A Edelman, NR Rao
Acta numerica 14, 233-297, 2005
6252005
The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices
F Benaych-Georges, RR Nadakuditi
Advances in Mathematics 227 (1), 494-521, 2011
5682011
The singular values and vectors of low rank perturbations of large rectangular random matrices
F Benaych-Georges, RR Nadakuditi
Journal of Multivariate Analysis 111, 120-135, 2012
3702012
Graph spectra and the detectability of community structure in networks
RR Nadakuditi, MEJ Newman
Physical review letters 108 (18), 188701, 2012
3582012
Sample eigenvalue based detection of high-dimensional signals in white noise using relatively few samples
RR Nadakuditi, A Edelman
IEEE Transactions on Signal Processing 56 (7), 2625-2638, 2008
3492008
Optshrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage
RR Nadakuditi
IEEE Transactions on Information Theory 60 (5), 3002-3018, 2014
1792014
Fundamental limit of sample generalized eigenvalue based detection of signals in noise using relatively few signal-bearing and noise-only samples
RR Nadakuditi, JW Silverstein
IEEE Journal of selected topics in Signal Processing 4 (3), 468-480, 2010
1772010
Mode control in a multimode fiber through acquiring its transmission matrix from a reference-less optical system
M N’Gom, TB Norris, E Michielssen, RR Nadakuditi
Optics letters 43 (3), 419-422, 2018
1092018
Spectra of random graphs with arbitrary expected degrees
RR Nadakuditi, MEJ Newman
Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 87 (1 …, 2013
962013
Statistical eigen-inference from large Wishart matrices
NR Rao, JA Mingo, R Speicher, A Edelman
922008
The polynomial method for random matrices
NR Rao, A Edelman
Foundations of Computational Mathematics 8, 649-702, 2008
912008
Low-rank and adaptive sparse signal (LASSI) models for highly accelerated dynamic imaging
S Ravishankar, BE Moore, RR Nadakuditi, JA Fessler
IEEE transactions on medical imaging 36 (5), 1116-1128, 2017
782017
Spectra of random graphs with community structure and arbitrary degrees
X Zhang, RR Nadakuditi, MEJ Newman
Physical review E 89 (4), 042816, 2014
632014
AngioNet: A convolutional neural network for vessel segmentation in X-ray angiography
K Iyer, CP Najarian, AA Fattah, CJ Arthurs, SMR Soroushmehr, V Subban, ...
Scientific Reports 11 (1), 18066, 2021
622021
Efficient sum of outer products dictionary learning (SOUP-DIL) and its application to inverse problems
S Ravishankar, RR Nadakuditi, JA Fessler
IEEE transactions on computational imaging 3 (4), 694-709, 2017
492017
Panoramic robust pca for foreground–background separation on noisy, free-motion camera video
BE Moore, C Gao, RR Nadakuditi
IEEE Transactions on Computational Imaging 5 (2), 195-211, 2019
482019
Multiplication of free random variables and the S-transform: The case of vanishing mean
NR Rao, R Speicher
442007
Low-rank spectral learning
A Kulesza, NR Rao, S Singh
Artificial Intelligence and Statistics, 522-530, 2014
422014
Controlling light transmission through highly scattering media using semi-definite programming as a phase retrieval computation method
M N’Gom, MB Lien, NM Estakhri, TB Norris, E Michielssen, RR Nadakuditi
Scientific reports 7 (1), 2518, 2017
412017
Passive radar detection with noisy reference channel using principal subspace similarity
S Gogineni, P Setlur, M Rangaswamy, RR Nadakuditi
IEEE Transactions on Aerospace and Electronic Systems 54 (1), 18-36, 2017
352017
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