Ranking-based Client Selection with Imitation Learning for Efficient Federated Learning
Federated Learning (FL) enables multiple devices to collaboratively train a shared model
while ensuring data privacy. The selection of participating devices in each training round …
while ensuring data privacy. The selection of participating devices in each training round …
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization
Federated Learning faces significant challenges in statistical and system heterogeneity,
along with high energy consumption, necessitating efficient client selection strategies …
along with high energy consumption, necessitating efficient client selection strategies …