Raj Rao Nadakuditi
Raj Rao Nadakuditi
Assistant Professor, University of Michigan
Email verificata su umich.edu
Citata da
Citata da
Random matrix theory
A Edelman, NR Rao
Acta numerica 14, 233, 2005
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
Graph spectra and the detectability of community structure in networks
RR Nadakuditi, MEJ Newman
Physical review letters 108 (18), 188701, 2012
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
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
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
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
Statistical eigen-inference from large Wishart matrices
NR Rao, JA Mingo, R Speicher, A Edelman
The Annals of Statistics 36 (6), 2850-2885, 2008
Spectra of random graphs with arbitrary expected degrees
RR Nadakuditi, MEJ Newman
Physical Review E 87 (1), 012803, 2013
The polynomial method for random matrices
NR Rao, A Edelman
Foundations of Computational Mathematics 8 (6), 649-702, 2008
Spectra of random graphs with community structure and arbitrary degrees
X Zhang, RR Nadakuditi, MEJ Newman
Physical Review E 89 (4), 042816, 2014
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
Low-rank spectral learning
A Kulesza, NR Rao, S Singh
Artificial Intelligence and Statistics, 522-530, 2014
Multiplication of free random variables and the S-transform: The case of vanishing mean
NR Rao, R Speicher
Electronic Communications in Probability 12, 248-258, 2007
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
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
On hard limits of eigen-analysis based planted clique detection
RR Nadakuditi
2012 IEEE Statistical Signal Processing Workshop (SSP), 129-132, 2012
Improved robust PCA using low-rank denoising with optimal singular value shrinkage
BE Moore, RR Nadakuditi, JA Fessler
2014 IEEE workshop on statistical signal processing (SSP), 13-16, 2014
Iterative, backscatter-analysis algorithms for increasing transmission and focusing light through highly scattering random media
C Jin, RR Nadakuditi, E Michielssen, SC Rand
JOSA A 30 (8), 1592-1602, 2013
Free probability, sample covariance matrices, and signal processing
NR Rao, A Edelman
2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006
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