Tag: fedstas

  • FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning

    FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning arXiv:2412.14226v1 Announce Type: cross Abstract: Federated learning (FL) is a machine learning methodology that involves the collaborative training of a global model across multiple decentralized clients in a privacy-preserving way. Several FL methods are introduced to tackle communication inefficiencies but do not address how…