Original title: FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning
Authors: Seongyoon Kim, Gihun Lee, Jaehoon Oh, Se-Young Yun
In the realm of decentralized learning, Federated Learning (FL) shields data while training models collaboratively. But lurking within this innovation lies a challenge: data diversity hampering performance.
Original article: https://arxiv.org/abs/2311.13267