2 papers
cs.CV2025
FedeCouple: Fine-Grained Balancing of Global-Generalization and Local-Adaptability in Federated Learning
Ming Yang, Dongrun Li, Xin Wang +5
In privacy-preserving mobile network transmission scenarios with heterogeneous client data, personalized federated learning methods that decouple feature extractors and classifiers…
cs.LG2025
PDSL: Privacy-Preserved Decentralized Stochastic Learning with Heterogeneous Data Distribution
Lina Wang, Yunsheng Yuan, Chunxiao Wang +1
In the paradigm of decentralized learning, a group of agents collaborates to learn a global model using distributed datasets without a central server. However, due to the heterogen…