29 citations · 29 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
ADP-VRSGP: Decentralized Learning with Adaptive Differential Privacy via Variance-Reduced Stochastic Gradient Push
Xiaoming Wu, Teng Liu, Xin Wang +2
Differential privacy is widely employed in decentralized learning to safeguard sensitive data by introducing noise into model updates. However, existing approaches that use fixed-v…
Choice Outweighs Effort: Facilitating Complementary Knowledge Fusion in Federated Learning via Re-calibration and Merit-discrimination
Ming Yang, Dongrun Li, Xin Wang +3
Cross-client data heterogeneity in federated learning induces biases that impede unbiased consensus condensation and the complementary fusion of generalization- and personalization…
FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization
Xiaoyang Yu, Xiaoming Wu, Xin Wang +3
Federated semantic segmentation enables pixel-level classification in images through collaborative learning while maintaining data privacy. However, existing research commonly over…