Derek Driggs
Derek Driggs
University of Cambridge
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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 (3), 199-217, 2021
A stochastic proximal alternating minimization for nonsmooth and nonconvex optimization
D Driggs, J Tang, J Liang, M Davies, CB Schonlieb
SIAM Journal on Imaging Sciences 14 (4), 1932-1970, 2021
Machine learning for COVID-19 diagnosis and prognostication: lessons for amplifying the signal while reducing the noise
D Driggs, I Selby, M Roberts, E Gkrania-Klotsas, JHF Rudd, G Yang, ...
Radiology: Artificial Intelligence 3 (4), e210011, 2021
Accelerating variance-reduced stochastic gradient methods
D Driggs, MJ Ehrhardt, CB Schönlieb
Mathematical Programming, 1-45, 2022
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
Tensor robust principal component analysis: Better recovery with atomic norm regularization
D Driggs, S Becker, J Boyd-Graber
arXiv preprint arXiv:1901.10991, 2019
On biased stochastic gradient estimation
D Driggs, J Liang, CB Schönlieb
Journal of Machine Learning Research 23 (24), 1-43, 2022
Adapting regularized low-rank models for parallel architectures
D Driggs, S Becker, A Aravkin
SIAM Journal on Scientific Computing 41 (1), A163-A189, 2019
P164 Using artificial intelligence to interrogate multi-national imaging datasets to determine the mechanism of COVID-19 pneumothorax
IA Selby, D Driggs, V Majcher, M Roberts, LE Sanchez, JHF Rudd, E Sala, ...
Thorax 77 (Suppl 1), A169-A170, 2022
A.-C. collaboration
D Driggs, I Selby, M Roberts, E Gkrania-Klotsas, JH Rudd, G Yang, ...
Machine Learning for COVID-19 Diagnosis and Prognostication: Lessons for …, 2021
AnySOS: An anytime algorithm for sos programming
D Driggs, H Fawzi
2019 IEEE 58th Conference on Decision and Control (CDC), 3012-3017, 2019
Practical Acceleration of the Condat-V\~ u Algorithm
D Driggs, MJ Ehrhardt, CB Schönlieb, J Tang
arXiv preprint arXiv:2403.17100, 2024
Accelerated Optimisation Algorithms for Machine Learning and Image Processing
D Driggs
Optimization for High-Dimensional Data Analysis
DT Driggs
University of Colorado at Boulder, 2017
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