16 citations · 52 across the 13 of their papers we have counts for
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cs.DC2025★ 4 cited
Enhancing Convergence, Privacy and Fairness for Wireless Personalized Federated Learning: Quantization-Assisted Min-Max Fair Scheduling
Xiyu Zhao, Qimei Cui, Ziqiang Du +6
Personalized federated learning (PFL) offers a solution to balancing personalization and generalization by conducting federated learning (FL) to guide personalized learning (PL). L…
cs.DC2025
Route-and-Aggregate Decentralized Federated Learning Under Communication Errors
Weicai Li, Tiejun Lv, Wei Ni +3
Decentralized federated learning (D-FL) allows clients to aggregate learning models locally, offering flexibility and scalability. Existing D-FL methods use gossip protocols, which…
cs.DC2024
Decentralized Federated Learning Over Imperfect Communication Channels
Weicai Li, Tiejun Lv, Wei Ni +3
This paper analyzes the impact of imperfect communication channels on decentralized federated learning (D-FL) and subsequently determines the optimal number of local aggregations p…