most citedGlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning

2 citations · 2 across the 2 of their papers we have counts for

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cs.LG2025

FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching

Qifan Yan, Andrew Liu, Shiqi He +2

Federated learning (FL) is a machine learning paradigm that facilitates massively distributed model training with end-user data on edge devices directed by a central server. Howeve…

cs.LG2022★ 2 cited

GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning

Shiqi He, Qifan Yan, Feijie Wu +3

Federated learning (FL) is an effective technique to directly involve edge devices in machine learning training while preserving client privacy. However, the substantial communicat…