DG-FedReuse enables cached updates from selected clients based on age-decayed proxy-gradient discrepancy in federated learning, with cache-age limits and fresh-client quotas
Read the original at arxiv.org→arXiv:2608.05358v1 Announce Type: new Abstract: Federated learning repeatedly incurs local optimization and model-update transmission. We study DG-FedReuse, a simulator-level mechanism that allows selected clients...
Original headline: "DG-FedReuse: Proxy-Gradient-Gated Cached-Update Reuse with Matched Sparse Uplink Accounting"
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- Aug 7, 04:00 UTC arXiv cs.LG lead source DG-FedReuse: Proxy-Gradient-Gated Cached-Update Reuse with Matched Sparse Uplink Accounting