2 papers
cs.LG2025
Competitive Advantage Attacks to Decentralized Federated Learning
Yuqi Jia, Minghong Fang, Neil Zhenqiang Gong
Decentralized federated learning (DFL) enables clients (e.g., hospitals and banks) to jointly train machine learning models without a central orchestration server. In each global t…
cs.LG2024
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
Haibo Yang, Peiwen Qiu, Prashant Khanduri +2
Existing works in federated learning (FL) often assume an ideal system with either full client or uniformly distributed client participation. However, in practice, it has been obse…