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Found 3 papers, 1 papers with code
Federated Learning for Cooperative Inference Systems: The Case of Early Exit Networks
As Internet of Things (IoT) technology advances, end devices like sensors and smartphones are progressively equipped with AI models tailored to their local memory and computational constraints.
FedStale: leveraging stale client updates in federated learning
Federated learning algorithms, such as FedAvg, are negatively affected by data heterogeneity and partial client participation.
Federated Learning under Heterogeneous and Correlated Client Availability
To this purpose, CA-Fed dynamically adapts the weight given to each client and may ignore clients with low availability and large correlation.
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