FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources

Federated Learning enables private collaborative intelligence across decentralized data sources, but multi-task scenarios face challenges due to device heterogeneity and resource inefficiency. FedACT is introduced as a novel resource heterogeneity-aware device scheduling approach to efficiently manage multiple concurrent FL jobs, aiming to minimize their average job completion time.