Author

Shiyue Hou

View on Semantic Scholar

1 paper indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

FedLDCS: Adaptive Divergence-Based Client Selection for Federated Learning

This paper proposes a novel Largest Distance Client Selection (LDCS) method that prioritizes clients based on the divergence of their local models from the global model, as quantified by the Frobenius norm, thereby improving training efficiency and model performance while overcoming the limitations of existing random or loss-based approaches.

Shiyue Hou, Zhenglun Kong · 2 citations