On five physical edge devices, asynchronous federated learning reached 75% accuracy about ten times faster than synchronous learning, but high-end devices supplied far more updates and accumulated up to roughly five times more privacy loss, while slow devices lost more accuracy under local…
Tifl: A tier-based federated learning system
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Empirical Analysis of Asynchronous Federated Learning on Heterogeneous Devices: Efficiency, Fairness, and Privacy Trade-offs
On five physical edge devices, asynchronous federated learning reached 75% accuracy about ten times faster than synchronous learning, but high-end devices supplied far more updates and accumulated up to roughly five times more privacy loss, while slow devices lost more accuracy under local…