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ORCIDRaj Rao Nadakuditi
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2020 – today
- 2023
[j20]Raj Rao Nadakuditi
, Hao Wu:
Free Component Analysis: Theory, Algorithms and Applications. Found. Comput. Math. 23(3): 973-1042 (2023)- [j19]Charles Bordenave, Simon Coste, Raj Rao Nadakuditi:
Detection Thresholds in Very Sparse Matrix Completion. Found. Comput. Math. 23(5): 1619-1743 (2023) - [j18]Rishi Sonthalia, Raj Rao Nadakuditi:
Training Data Size Induced Double Descent For Denoising Feedforward Neural Networks and the Role of Training Noise. Trans. Mach. Learn. Res. 2023 (2023) - 2020
- [j17]Arvind Prasadan, Raj Rao Nadakuditi:
Time Series Source Separation Using Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. 19(2): 1160-1199 (2020) - [j16]Brian E. Moore, Saiprasad Ravishankar, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Online Adaptive Image Reconstruction (OnAIR) Using Dictionary Models. IEEE Trans. Computational Imaging 6: 153-166 (2020)
2010 – 2019
- 2019
- [j15]Brian E. Moore, Chen Gao, Raj Rao Nadakuditi:
Panoramic Robust PCA for Foreground-Background Separation on Noisy, Free-Motion Camera Video. IEEE Trans. Computational Imaging 5(2): 195-211 (2019) - [j14]Andrew John Wagenmaker, Brian E. Moore, Raj Rao Nadakuditi:
Robust Photometric Stereo via Dictionary Learning. IEEE Trans. Computational Imaging 5(2): 212-227 (2019) - [c33]Arvind Prasadan, Asad Lodhia, Raj Rao Nadakuditi:
Phase Transitions in the Dynamic Mode Decomposition Algorithm. CAMSAP 2019: 396-400 - [i20]M. E. J. Newman, Xiao Zhang, Raj Rao Nadakuditi:
Spectra of random networks with arbitrary degrees. CoRR abs/1901.02029 (2019) - [i19]Arvind Prasadan, Raj Rao Nadakuditi:
Time Series Source Separation using Dynamic Mode Decomposition. CoRR abs/1903.01310 (2019) - [i18]Hao Wu, Raj Rao Nadakuditi:
Free Component Analysis: Theory, Algorithms & Applications. CoRR abs/1905.01713 (2019) - [i17]Arvind Prasadan, Raj Rao Nadakuditi, Debashis Paul:
Sparse Equisigned PCA: Algorithms and Performance Bounds in the Noisy Rank-1 Setting. CoRR abs/1905.09369 (2019) - 2018
- [j13]Sandeep Gogineni, Pawan Setlur, Muralidhar Rangaswamy, Raj Rao Nadakuditi:
Passive Radar Detection With Noisy Reference Channel Using Principal Subspace Similarity. IEEE Trans. Aerosp. Electron. Syst. 54(1): 18-36 (2018) - [c32]Arvind Prasadan, Raj Rao Nadakuditi:
The Finite Sample Performance of Dynamic Mode Decomposition. GlobalSIP 2018: 286-290 - [c31]Moussa N'Gom, Theodore B. Norris, Eric Michielssen, Raj Rao Nadakuditi:
Reference-less Method for Computing the Transmission Matrix of a Multimode Fiber. OFC 2018: 1-3 - [i16]Brian E. Moore, Saiprasad Ravishankar, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Online Adaptive Image Reconstruction (OnAIR) Using Dictionary Models. CoRR abs/1809.01817 (2018) - 2017
- [j12]Saiprasad Ravishankar, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) and Its Application to Inverse Problems. IEEE Trans. Computational Imaging 3(4): 694-709 (2017) - [j11]Nicholas Asendorf, Raj Rao Nadakuditi:
Improved Detection of Correlated Signals in Low-Rank-Plus-Noise Type Data Sets Using Informative Canonical Correlation Analysis (ICCA). IEEE Trans. Inf. Theory 63(6): 3451-3467 (2017) - [j10]Saiprasad Ravishankar, Brian E. Moore, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging. IEEE Trans. Medical Imaging 36(5): 1116-1128 (2017) - [c30]Saiprasad Ravishankar, Brian E. Moore, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Efficient online dictionary adaptation and image reconstruction for dynamic MRI. ACSSC 2017: 835-839 - [c29]Chen Gao, Brian E. Moore, Raj Rao Nadakuditi:
Augmented robust PCA for foreground-background separation on noisy, moving camera video. GlobalSIP 2017: 1240-1244 - [c28]Andrew J. Wagenmaker, Brian E. Moore, Raj Rao Nadakuditi:
Robust surface reconstruction from gradients via adaptive dictionary regularization. ICIP 2017: 1002-1006 - [c27]Andrew J. Wagenmaker, Brian E. Moore, Raj Rao Nadakuditi:
Robust photometric stereo using learned image and gradient dictionaries. ICIP 2017: 1457-1461 - [i15]Chen Gao, Brian E. Moore, Raj Rao Nadakuditi:
Augmented Robust PCA For Foreground-Background Separation on Noisy, Moving Camera Video. CoRR abs/1709.09328 (2017) - [i14]Andrew J. Wagenmaker, Brian E. Moore, Raj Rao Nadakuditi:
Robust Photometric Stereo Using Learned Image and Gradient Dictionaries. CoRR abs/1710.00002 (2017) - [i13]Andrew J. Wagenmaker, Brian E. Moore, Raj Rao Nadakuditi:
Robust Surface Reconstruction from Gradients via Adaptive Dictionary Regularization. CoRR abs/1710.00230 (2017) - [i12]Andrew J. Wagenmaker, Brian E. Moore, Raj Rao Nadakuditi:
Robust Photometric Stereo via Dictionary Learning. CoRR abs/1710.08873 (2017) - [i11]Brian E. Moore, Chen Gao, Raj Rao Nadakuditi:
Panoramic Robust PCA for Foreground-Background Separation on Noisy, Free-Motion Camera Video. CoRR abs/1712.06229 (2017) - 2016
- [c26]Hao Wu, Raj Rao Nadakuditi:
Free component analysis. ACSSC 2016: 85-89 - [c25]Brian E. Moore, Raj Rao Nadakuditi:
Robust PCA: Low rank matrix estimation with hard or soft thresholding-based outlier rejection. GlobalSIP 2016: 80-84 - [c24]Saiprasad Ravishankar, Brian E. Moore, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Efficient learning of dictionaries with low-rank atoms. GlobalSIP 2016: 222-226 - [c23]Saiprasad Ravishankar, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Sum of outer products dictionary learning for inverse problems. GlobalSIP 2016: 1142-1146 - [c22]Saiprasad Ravishankar, Brian E. Moore, Raj Rao Nadakuditi, Jeffrey A. Fessler:
LASSI: A low-rank and adaptive sparse signal model for highly accelerated dynamic imaging. IVMSP 2016: 1-5 - [c21]Sandeep Gogineni, Pawan Setlur, Muralidhar Rangaswamy, Raj Rao Nadakuditi:
Comparison of passive radar detectors with noisy reference signal. SSP 2016: 1-5 - [i10]Saiprasad Ravishankar, Brian E. Moore, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging. CoRR abs/1611.04069 (2016) - 2015
- [j9]Raj Tejas Suryaprakash, Raj Rao Nadakuditi:
Consistency and MSE Performance of MUSIC-Based DOA of a Single Source in White Noise With Randomly Missing Data. IEEE Trans. Signal Process. 63(18): 4756-4770 (2015) - [c20]Nicholas Asendorf, Raj Rao Nadakuditi:
Improving multiset canonical correlation analysis in high dimensional sample deficient settings. ACSSC 2015: 112-116 - [c19]Nicholas Asendorf, Raj Rao Nadakuditi:
Fundamental limits of singular value based signal detection from randomly compressed signal-plus-noise matrices. ACSSC 2015: 1467-1471 - [c18]Himanshu Nayar, Benjamin A. Miller, Kelly Geyer, Rajmonda Sulo Caceres, Steven Thomas Smith, Raj Rao Nadakuditi:
Improved hidden clique detection by optimal linear fusion of multiple adjacency matrices. ACSSC 2015: 1520-1524 - [c17]Nicholas Asendorf, Raj Rao Nadakuditi:
Improved estimation of canonical vectors in canonical correlation analysis. ACSSC 2015: 1806-1810 - [c16]Raj Tejas Suryaprakash, Raj Rao Nadakuditi:
Algorithms for estimation of low-rank matrices with triple Kronecker structured singular vectors. CAMSAP 2015: 121-124 - [c15]Himanshu Nayar, Raj Rao Nadakuditi:
OptFuse: Low-rank factor estimation by optimal data-driven linear fusion of multiple signal-plus-noise matrices. FUSION 2015: 15-21 - [c14]Sandeep Gogineni, Pawan Setlur, Muralidhar Rangaswamy, Raj Rao Nadakuditi:
Random matrix theory inspired passive bistatic radar detection with noisy reference signal. ICASSP 2015: 2754-2758 - [c13]Raj Tejas Suryaprakash, Brian E. Moore, Raj Rao Nadakuditi:
Algorithms and performance analysis for estimation of low-rank matrices with Kronecker structured singular vectors. ICASSP 2015: 3776-3780 - [i9]Saiprasad Ravishankar, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Efficient Sum of Sparse Outer Products Dictionary Learning (SOUP-DIL). CoRR abs/1511.06333 (2015) - [i8]Saiprasad Ravishankar, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Efficient Sum of Outer Products Dictionary Learning (SOUP-DIL) - The $\ell_0$ Method. CoRR abs/1511.08842 (2015) - 2014
- [j8]Jinho Baik, Raj Rao Nadakuditi:
Batch latency analysis and phase transitions for a tandem of queues with exponentially distributed service times. Queueing Syst. Theory Appl. 78(3): 255-285 (2014) - [j7]Raj Rao Nadakuditi:
OptShrink: An Algorithm for Improved Low-Rank Signal Matrix Denoising by Optimal, Data-Driven Singular Value Shrinkage. IEEE Trans. Inf. Theory 60(5): 3002-3018 (2014) - [c12]Himanshu Nayar, Raj Rao Nadakuditi:
Theoretical performance analysis of Tucker Higher Order SVD in extracting structure from multiple signal-plus-noise matrices. ACSSC 2014: 755-759 - [c11]Brian E. Moore, Raj Rao Nadakuditi, Jeffrey A. Fessler:
Improved Robust PCA using low-rank denoising with optimal singular value shrinkage. SSP 2014: 13-16 - [i7]Jinho Baik, Raj Rao Nadakuditi:
Batch latency analysis and phase transitions for a tandem of queues with exponentially distributed service times. CoRR abs/1403.2400 (2014) - 2013
- [j6]Raj Rao Nadakuditi, Igor L. Markov:
On bottleneck analysis in stochastic stream processing. ACM Trans. Design Autom. Electr. Syst. 18(3): 34:1-34:20 (2013) - [j5]Nicholas Asendorf, Raj Rao Nadakuditi:
The Performance of a Matched Subspace Detector That Uses Subspaces Estimated From Finite, Noisy, Training Data. IEEE Trans. Signal Process. 61(8): 1972-1985 (2013) - [i6]Raj Rao Nadakuditi:
When are the most informative components for inference also the principal components? CoRR abs/1302.1232 (2013) - [i5]Raj Rao Nadakuditi:
Optimally weighted recovery of a low-rank signal matrix from a high-dimensional signal-plus-noise matrix. CoRR abs/1306.6042 (2013) - [i4]Xiao Zhang, Raj Rao Nadakuditi, Mark E. J. Newman:
Spectra of random graphs with community structure and arbitrary degrees. CoRR abs/1310.0046 (2013) - 2012
- [j4]Florent Benaych-Georges, Raj Rao Nadakuditi:
The singular values and vectors of low rank perturbations of large rectangular random matrices. J. Multivar. Anal. 111: 120-135 (2012) - [c10]Curtis Jin, Raj Rao Nadakuditi, Eric Michielssen, Stephen Rand:
An iterative, backscatter-analysis based algorithm for increasing transmission through a highly-backscattering random medium. SSP 2012: 97-100 - [c9]Raj Rao Nadakuditi:
On hard limits of eigen-analysis based planted clique detection. SSP 2012: 129-132 - [c8]Nicholas Asendorf, Raj Tejas Suryaprakash, Raj Rao Nadakuditi:
The performance of deterministic matched subspace detectors when using subspaces estimated from noisy, missing data. SSP 2012: 397-400 - [c7]Raj Tejas Suryaprakash, Raj Rao Nadakuditi:
The performance of music-based DOA in white noise with missing data. SSP 2012: 800-803 - [i3]Raj Rao Nadakuditi, M. E. J. Newman:
Graph spectra and the detectability of community structure in networks. CoRR abs/1205.1813 (2012) - [i2]Raj Rao Nadakuditi, M. E. J. Newman:
Spectra of random graphs with arbitrary expected degrees. CoRR abs/1208.1275 (2012) - 2011
- [c6]Raj Rao Nadakuditi:
Exploiting random matrix theory to improve noisy low-rank matrix approximation. ACSCC 2011: 769-773 - [c5]Arnau Tibau Puig, Ami Wiesel, Raj Rao Nadakuditi, Alfred O. Hero III:
Misaligned Principal Components Analysis: Application to gene expression time series analysis. ACSCC 2011: 1002-1006 - [c4]Nicholas Asendorf, Raj Rao Nadakuditi:
Improving and characterizing the performance of stochastic matched subspace detectors when using noisy estimated subspaces. ACSCC 2011: 1893-1897 - [c3]Raj Rao Nadakuditi, Mingyan Liu:
Latency-optimizing file splitting for transmission over a large multi-hop network. ITA 2011: 290-295 - 2010
- [j3]Raj R. Nadakuditi, Jack W. Silverstein:
Fundamental Limit of Sample Generalized Eigenvalue Based Detection of Signals in Noise Using Relatively Few Signal-Bearing and Noise-Only Samples. IEEE J. Sel. Top. Signal Process. 4(3): 468-480 (2010) - [c2]Raj R. Nadakuditi, Igor L. Markov:
On the costs and benefits of stochasticity in stream processing. DAC 2010: 320-325
2000 – 2009
- 2009
- [i1]Raj R. Nadakuditi, Jack W. Silverstein:
Fundamental limit of sample generalized eigenvalue based detection of signals in noise using relatively few signal-bearing and noise-only samples. CoRR abs/0902.4250 (2009) - 2008
- [j2]Raj Rao Nadakuditi, Alan Edelman:
Sample Eigenvalue Based Detection of High-Dimensional Signals in White Noise Using Relatively Few Samples. IEEE Trans. Signal Process. 56(7-1): 2625-2638 (2008) - 2006
- [b1]Raj Rao Nadakuditi:
Applied stochastic Eigen-analysis. Massachusetts Institute of Technology, Cambridge, MA, USA, 2006 - 2005
- [c1]Raj R. Nadakuditi, Alan Edelman:
The bias of the MVDR beamformer outputs under diagonal loading. ICASSP (4) 2005: 793-796 - 2004
- [j1]Raj R. Nadakuditi, James C. Preisig:
A channel subspace post-filtering approach to adaptive least-squares estimation. IEEE Trans. Signal Process. 52(7): 1901-1914 (2004)
Coauthor Index
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