Mitigating the Communication Straggler Effect in Federated Learning via Named Data Networking
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DOI: 10.1109/mcom.001.2300419
Abstract: Federated learning (FL) has emerged as a prominent solution that enables distributed training of machine learning (ML) models at multiple end-devices with their own data samples. The FL performance, and in particular, the training convergence… read more here.
Keywords: communication straggler; named data; data networking; mitigating communication ... See more keywords