Yingxin Liu

Empowering Non-IID Federated Learning With Data Augmentation and Data-Free Knowledge Distillation

Federated learning (FL) is an emerging distributed machine learning framework that enables collaborative learning among multiple parties while preserving data privacy. However, the complexity of environments and node heterogeneity in the real world result in uneven data distribution across nodes, leading to Non-IID (No...