FedHAW dynamically adjusts aggregation weights in federated learning via hypergradient descent, yielding better generalization under data heterogeneity and robustness to communication errors.
Personalized federated learning for intelligent IoT applications: A cloud-edge based framework,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Federated Learning with Hypergradient-based Online Update of Aggregation Weights
FedHAW dynamically adjusts aggregation weights in federated learning via hypergradient descent, yielding better generalization under data heterogeneity and robustness to communication errors.