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Bubacarr Bah
Bubacarr Bah
Associate Professor and Head of Data Science, MRC Unit The Gambia at London School of Hygiene
Verified email at lshtm.ac.uk - Homepage
Title
Cited by
Cited by
Year
Improved bounds on restricted isometry constants for Gaussian matrices
B Bah, J Tanner
SIAM Journal on Matrix Analysis and Applications 31 (5), 2882-2898, 2010
1002010
Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers
B Bah, H Rauhut, U Terstiege, M Westdickenberg
Information and Inference: A Journal of the IMA 11 (1), 307-353, 2022
852022
Vanishingly sparse matrices and expander graphs, with application to compressed sensing
B Bah, J Tanner
IEEE transactions on information theory 59 (11), 7491-7508, 2013
322013
Diffusion maps: analysis and applications
B Bah
University of Oxford; Mathematical Institute, 2008
282008
Model-based sketching and recovery with expanders
B Bah, L Baldassarre, V Cevher
Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete …, 2014
232014
Practical high-throughput, non-adaptive and noise-robust SARS-CoV-2 testing
HB Petersen, B Bah, P Jung
arXiv preprint arXiv:2007.09171, 3, 2020
212020
The sample complexity of weighted sparse approximation
B Bah, R Ward
IEEE Transactions on Signal Processing 64 (12), 3145-3155, 2016
212016
Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices
B Bah, J Tanner
Linear Algebra and its Applications 441, 88-109, 2014
202014
Energy-aware adaptive bi-Lipschitz embeddings
B Bah, A Sadeghian, V Cevher
arXiv preprint arXiv:1307.3457, 2013
192013
Recent methodological advances in federated learning for healthcare
F Zhang, D Kreuter, Y Chen, S Dittmer, S Tull, T Shadbahr, M Schut, ...
Patterns 5 (6), 2024
142024
On error correction neural networks for economic forecasting
M Mvubu, E Kabuga, C Plitz, B Bah, R Becker, HG Zimmermann
2020 IEEE 23rd International Conference on Information Fusion (FUSION), 1-8, 2020
102020
Efficient and robust mixed-integer optimization methods for training binarized deep neural networks
J Kurtz, B Bah
arXiv preprint arXiv:2110.11382, 2021
92021
An integer programming approach to deep neural networks with binary activation functions
B Bah, J Kurtz
arXiv preprint arXiv:2007.03326, 2020
82020
Metric learning with rank and sparsity constraints
B Bah, S Becker, V Cevher, B Gözcü
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
82014
Efficient Tuning-Free l 1-Regression of Nonnegative Compressible Signals
HB Petersen, B Bah, P Jung
Frontiers in Applied Mathematics and Statistics 7, 615573, 2021
72021
Efficient noise-blind -regression of nonnegative compressible signals
H Petersen, B Bah, P Jung
arXiv preprint arXiv:2003.13092, 2020
72020
Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness
E Muller, JP Shock, A Bender, J Kleeberger, T Högen, M Rosenfelder, ...
Computers in Biology and Medicine 107, 145-152, 2019
72019
On the construction of sparse matrices from expander graphs
B Bah, J Tanner
Frontiers in Applied Mathematics and Statistics 4, 39, 2018
72018
Discrete optimization methods for group model selection in compressed sensing
B Bah, J Kurtz, O Schaudt
Mathematical Programming 190, 171-220, 2021
62021
Improving the reliability of pooled testing with combinatorial decoding and compressed sensing
HB Petersen, S Agarwal, P Jung, B Bah
2021 55th Annual Conference on Information Sciences and Systems (CISS), 1-5, 2021
52021
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