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Waheed U. Bajwa
Waheed U. Bajwa
Professor of Electrical & Computer Engineering and Statistics, Rutgers University
Verified email at rutgers.edu - Homepage
Title
Cited by
Cited by
Year
Compressed channel sensing: A new approach to estimating sparse multipath channels
WU Bajwa, J Haupt, AM Sayeed, R Nowak
Proceedings of the IEEE 98 (6), 1058-1076, 2010
13422010
Compressed sensing for networked data
J Haupt, WU Bajwa, M Rabbat, R Nowak
IEEE Signal Processing Mag. 25 (2), 92-101, 2008
7212008
Toeplitz compressed sensing matrices with applications to sparse channel estimation
J Haupt, WU Bajwa, G Raz, R Nowak
IEEE Trans. Inform. Theory 56 (11), 5862-5875, 2010
5702010
Compressive wireless sensing
WU Bajwa, J Haupt, A Sayeed, R Nowak
Proc. 5th Int. Conf. Information Processing in Sensor Networks (IPSN'06 …, 2006
4812006
Toeplitz-structured compressed sensing matrices
WU Bajwa, JD Haupt, GM Raz, SJ Wright, RD Nowak
Proc. 14th IEEE/SP Workshop Statistical Signal Processing (SSP'07), 294-298, 2007
4372007
Compressed channel sensing
WU Bajwa, J Haupt, G Raz, R Nowak
Proc. 42nd Annu. Conf. Information Sciences and Systems (CISS’08), 5-10, 2008
2902008
Joint source–channel communication for distributed estimation in sensor networks
WU Bajwa, J Haupt, A Sayeed, R Nowak
IEEE Trans. Inform. Theory 53 (10), 3629-3653, 2007
2232007
Identification of parametric underspread linear systems and super-resolution radar
WU Bajwa, K Gedalyahu, Y Eldar
IEEE Trans. Signal Processing 59 (6), 2548-2561, 2011
1682011
ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning
Z Yang, WU Bajwa
IEEE Trans. Signal Inform. Proc. over Netw. 5 (4), 611–627, 2019
1472019
Cloud K-SVD: A collaborative dictionary learning algorithm for big, distributed data
H Raja, WU Bajwa
IEEE Trans. Signal Processing 64 (1), 173-188, 2016
1192016
Sparse multipath channels: Modeling and estimation
WU Bajwa, A Sayeed, R Nowak
Proc. 13th IEEE Digital Signal Processing Workshop, 320-325, 2009
1132009
Adversary-resilient distributed and decentralized statistical inference and machine learning: An overview of recent advances under the Byzantine threat model
Z Yang, A Gang, WU Bajwa
IEEE Signal Processing Mag. 37 (3), 146-159, 2020
107*2020
Why Gabor frames? Two fundamental measures of coherence and their role in model selection
WU Bajwa, R Calderbank, S Jafarpour
J. Commun. Netw. 12 (4), 289-307, 2010
1072010
Learning sparse doubly-selective channels
WU Bajwa, AM Sayeed, R Nowak
Proc. 46th Annu. Allerton Conf. Communication, Control, and Computing, 575-582, 2008
1042008
BRIDGE: Byzantine-resilient decentralized gradient descent
C Fang, Z Yang, WU Bajwa
IEEE Transactions on Signal and Information Processing over Networks 8, 610-626, 2022
1032022
MIMO-MC radar: A MIMO radar approach based on matrix completion
S Sun, WU Bajwa, AP Petropulu
IEEE Trans. Aerosp. Electron. Syst. 51 (3), 1839-1852, 2015
922015
Posterior consistency in linear models under shrinkage priors
A Armagan, DB Dunson, J Lee, WU Bajwa, N Strawn
Biometrika 100 (4), 1011-1018, 2013
912013
Asynchronous code-division random access using convex optimization
L Applebaum, WU Bajwa, MF Duarte, R Calderbank
Physical Communication 5 (2), 129-147, 2012
902012
Matched source-channel communication for field estimation in wireless sensor networks
WU Bajwa, A Sayeed, R Nowak
Proc. 4th Intl. Conf. Information Processing in Sensor Networks (IPSN’05 …, 2005
842005
Two are better than one: Fundamental parameters of frame coherence
WU Bajwa, R Calderbank, DG Mixon
Appl. Comput. Harmon. Anal. 33 (1), 58-78, 2012
832012
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