2026
Communication-Efficient Heterogeneous Federated Learning with Sparse Prototypes in Resource-Constrained Environments
AAAI 2026technical
Communication efficiency in federated learning (FL) remains a critical challenge in resource-constrained environments. While prototype-based FL reduces communication overhead by sharing class prototypes—mean activations in the penultimate layer—instead of model parameters, its efficiency degrades wi