5 citations · 9 across the 7 of their papers we have counts for
4 papers · 1 filter
On the Fast Adaptation of Delayed Clients in Decentralized Federated Learning: A Centroid-Aligned Distillation Approach
Jiahui Bai, Hai Dong, A. K. Qin
Decentralized Federated Learning (DFL) struggles with the slow adaptation of late-joining delayed clients and high communication costs in asynchronous environments. These limitatio…
Bridging Generalization Gap of Heterogeneous Federated Clients Using Generative Models
Ziru Niu, Hai Dong, A. K. Qin
Federated Learning (FL) is a privacy-preserving machine learning framework facilitating collaborative training across distributed clients. However, its performance is often comprom…
CHASE: A Causal Hypergraph based Framework for Root Cause Analysis in Multimodal Microservice Systems
Ziming Zhao, Zhenwei Wang, Tiehua Zhang +7
In recent years, the widespread adoption of distributed microservice architectures within the industry has significantly increased the demand for enhanced system availability and r…
FedSPU: Personalized Federated Learning for Resource-constrained Devices with Stochastic Parameter Update
Ziru Niu, Hai Dong, A. K. Qin
Personalized Federated Learning (PFL) is widely employed in IoT applications to handle high-volume, non-iid client data while ensuring data privacy. However, heterogeneous edge dev…