Federated Representation Learning for Heterogeneous Data
Federated learning provides a promising paradigm for collaborative model training among mutually untrusted parties without sharing local data. However, data distributions in real-world federated scenarios are usually heterogeneous, which can significantly degrade global model performance. Existing approaches mainly add...