Derek Driggs
Derek Driggs
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Zitiert von
Zitiert von
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
Nature Machine Intelligence 3, 199–217, 2021
The asymptotic equivalence of fixed heat flux and fixed temperature thermal boundary conditions for rapidly rotating convection
MA Calkins, K Hale, K Julien, D Nieves, D Driggs, P Marti
Journal of Fluid Mechanics 784 (R2), 2015
Adapting regularized low-rank models for parallel architectures
D Driggs, S Becker, A Aravkin
SIAM Journal on Scientific Computing 41 (1), A163-A189, 2019
SPRING: A fast stochastic proximal alternating method for non-smooth non-convex optimization
D Driggs, J Tang, J Liang, M Davies, CB Schönlieb
arXiv preprint arXiv:2002.12266, 2020
Tensor robust principal component analysis: Better recovery with atomic norm regularization
D Driggs, S Becker, J Boyd-Graber
arXiv preprint arXiv:1901.10991, 2019
Accelerating variance-reduced stochastic gradient methods
D Driggs, MJ Ehrhardt, CB Schönlieb
Mathematical Programming, 1-45, 2020
Machine learning for COVID-19 diagnosis and prognostication: lessons for amplifying the signal whilst reducing the noise
D Driggs, IA Selby, M Roberts, E Gkrania-Klotsas, J Rudd, G Yang, ...
Radiology: Artificial Intelligence, 2021
AnySOS: An anytime algorithm for SOS programming
D Driggs, H Fawzi
2019 IEEE 58th Conference on Decision and Control (CDC), 3012-3017, 2019
On Biased Stochastic Gradient Estimation
D Driggs, J Liang, CB Schönlieb
arXiv preprint arXiv:1906.01133, 2019
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