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Found 4 papers, 3 papers with code
High-Performance Statistical Computing in the Computing Environments of the 2020s
To our knowledge, this is the first demonstration of the feasibility of penalized regression of survival outcomes at this scale.
Computation
Splitting with Near-Circulant Linear Systems: Applications to Total Variation CT and PET
Many imaging problems, such as total variation reconstruction of X-ray computed tomography (CT) and positron-emission tomography (PET), are solved via a convex optimization problem with near-circulant, but not actually circulant, linear systems.
Optimization and Control
Easily parallelizable and distributable class of algorithms for structured sparsity, with optimal acceleration
From this unification we propose a continuum of preconditioned forward-backward operator splitting algorithms amenable to parallel and distributed computing.
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks
Experiments in particle physics produce enormous quantities of data that must be analyzed and interpreted by teams of physicists.
