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Found 3 papers, 1 papers with code
MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent
Federated learning enables multiple, distributed participants (potentially on different clouds) to collaborate and train machine/deep learning models by sharing parameters/gradients.
Nonparametric Deconvolution Models
This uniquely allows NDMs both to deconvolve each observation into its constituent factors, and also to describe how the factor distributions specific to each observation vary across observations and deviate from the corresponding global factors.
FfDL : A Flexible Multi-tenant Deep Learning Platform
This paper describes the design, implementation and our experiences with FfDL, a DL platform used at IBM.
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