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cs.LG2025★ 1 cited
STHFL: Spatio-Temporal Heterogeneous Federated Learning
Shunxin Guo, Hongsong Wang, Shuxia Lin +2
Federated learning is a new framework that protects data privacy and allows multiple devices to cooperate in training machine learning models. Previous studies have proposed multip…
cs.LG2024
Addressing Skewed Heterogeneity via Federated Prototype Rectification with Personalization
Shunxin Guo, Hongsong Wang, Shuxia Lin +2
Federated learning is an efficient framework designed to facilitate collaborative model training across multiple distributed devices while preserving user data privacy. A significa…
cs.LG2023
Dynamic Heterogeneous Federated Learning with Multi-Level Prototypes
Shunxin Guo, Hongsong Wang, Xin Geng
Federated learning shows promise as a privacy-preserving collaborative learning technique. Existing heterogeneous federated learning mainly focuses on skewing the label distributio…