An adaptive federated few-shot learning method with intelligent device selection
Federated learning, which enables the training of intelligent models without transferring data and solely by relying on the computational capabilities of distributed devices, faces significant challenges in few-shot scenarios due to data heterogeneity, resource constraints, and slow convergence. The primary obstacle li...
Fazeleh Tavassolian, Mahdi Abbasi, Atefeh Salimi Shahraki et al.
· Scientific Reports · 0 citations