Artikler med krav om offentlig adgang - Waheed U. BajwaFå flere oplysninger
Tilgængelige et sted: 69
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
Krav: US National Science Foundation, US Department of Defense
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
Krav: US National Science Foundation
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
Krav: US National Science Foundation, US Department of Defense
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
Krav: US National Science Foundation, US Department of Defense
Posterior consistency in linear models under shrinkage priors
A Armagan, DB Dunson, J Lee, WU Bajwa, N Strawn
Biometrika 100 (4), 1011-1018, 2013
Krav: US National Institutes of Health
Computational imaging with a highly parallel image-plane-coded architecture: Challenges and solutions
JP Dumas, MA Lodhi, WU Bajwa, MC Pierce
Optics Express 24 (6), 6145-6155, 2016
Krav: US National Science Foundation
Tensor regression using low-rank and sparse Tucker decompositions
T Ahmed, H Raja, WU Bajwa
SIAM J. Math. Data Science 2 (4), 944-966, 2020
Krav: US National Science Foundation, US Department of Defense
A low tensor-rank representation approach for clustering of imaging data
T Wu, WU Bajwa
IEEE Signal Processing Letters 25 (8), 1196-1200, 2018
Krav: US National Science Foundation, US Department of Defense
A linearly convergent algorithm for distributed principal component analysis
A Gang, WU Bajwa
EURASIP J. Signal Processing 193, 108408, 2022
Krav: US National Science Foundation, US Department of Defense
Computational endoscopy—a framework for improving spatial resolution in fiber bundle imaging
JP Dumas, MA Lodhi, BA Taki, WU Bajwa, MC Pierce
Optics Letters 44 (16), 3968-3971, 2019
Krav: US National Science Foundation
Fast and communication-efficient distributed PCA
A Gang, H Raja, WU Bajwa
Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP'19 …, 2019
Krav: US National Science Foundation, US Department of Defense
Minimax lower bounds on dictionary learning for tensor data
Z Shakeri, WU Bajwa, AD Sarwate
IEEE Trans. Inform. Theory 64 (4), 2706-2726, 2018
Krav: US National Science Foundation, US Department of Defense
Passive RFID for object and use detection during trauma resuscitation
S Parlak, I Marsic, A Sarcevic, WU Bajwa, LJ Waterhouse, RS Burd
IEEE Trans. Mobile Computing 15 (4), 924-937, 2016
Krav: US National Science Foundation
Minimax lower bounds for Kronecker-structured dictionary learning
Z Shakeri, WU Bajwa, AD Sarwate
Proc. IEEE Intl. Symp. Information Theory (ISIT'16), Barcelona, Spain, 1148-1152, 2016
Krav: US National Science Foundation
Scaling-up distributed processing of data streams for machine learning
M Nokleby, H Raja, WU Bajwa
Proc. of the IEEE 108 (11), 1984-2012, 2020
Krav: US National Science Foundation, US Department of Defense
STARK: Structured dictionary learning through rank-one tensor recovery
M Ghassemi, Z Shakeri, AD Sarwate, WU Bajwa
Proc. 7th Intl. Workshop Computational Advances in Multi-Sensor Adaptive …, 2017
Krav: US National Science Foundation, US Department of Defense
Learning mixtures of separable dictionaries for tensor data: Analysis and algorithms
M Ghassemi, Z Shakeri, AD Sarwate, WU Bajwa
IEEE Trans. Signal Processing 68, 33-48, 2020
Krav: US National Science Foundation, US Department of Defense, US National …
Distributed principal subspace analysis for partitioned big data: Algorithms, analysis, and implementation
A Gang, B Xiang, WU Bajwa
IEEE Trans. Signal Inform. Proc. over Netw. 7, 699-715, 2021
Krav: US National Science Foundation, US Department of Defense
Detection theory for union of subspaces
MA Lodhi, WU Bajwa
IEEE Trans. Signal Processing 66 (24), 6347-6362, 2018
Krav: US National Science Foundation, US Department of Defense
FAST-PCA: A fast and exact algorithm for distributed principal component analysis
A Gang, WU Bajwa
IEEE Transactions on Signal Processing 70, 6080-6095, 2022
Krav: US National Science Foundation, US Department of Defense
Oplysninger om publikation og økonomisk støtte registreres automatisk af et computerprogram