2 citations · 3 across the 8 of their papers we have counts for
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cs.DC2026
FWeb3: A Practical Incentive-Aware Federated Learning Framework
Peishen Yan, Shuang Liang, Yang Hua +9
Federated learning (FL) enables collaborative model training over distributed private data. However, sustaining open participation requires incentive mechanisms that compensate con…
cs.DC2025
FedCod: An Efficient Communication Protocol for Cross-Silo Federated Learning with Coding
Peishen Yan, Jun Li, Hao Wang +4
Federated Learning (FL) is an innovative distributed machine learning paradigm that enables multiple parties to collaboratively train a model without sharing their raw data, thereb…
cs.DC2024★ 2 cited
OFL-W3: A One-shot Federated Learning System on Web 3.0
Linshan Jiang, Moming Duan, Bingsheng He +4
Federated Learning (FL) addresses the challenges posed by data silos, which arise from privacy, security regulations, and ownership concerns. Despite these barriers, FL enables the…