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Found 2 papers, 2 papers with code
MP-SL: Multihop Parallel Split Learning
Moreover, the task of training ML models with a vast number of parameters demands computing and memory resources beyond the capabilities of small devices, such as mobile and Internet of Things (IoT) devices.
IPLS : A Framework for Decentralized Federated Learning
The proliferation of resourceful mobile devices that store rich, multidimensional and privacy-sensitive user data motivate the design of federated learning (FL), a machine-learning (ML) paradigm that enables mobile devices to produce an ML model without sharing their data.
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