177 citations · 425 across the 19 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.CR2020★ 3 cited
Federated Crowdsensing: Framework and Challenges
Leye Wang, Han Yu, Xiao Han
Crowdsensing is a promising sensing paradigm for smart city applications (e.g., traffic and environment monitoring) with the prevalence of smart mobile devices and advanced network…
cs.GT2020★ 22 cited
A VCG-based Fair Incentive Mechanism for Federated Learning
Mingshu Cong, Han Yu, Xi Weng +3
The enduring value of the Vickrey-Clarke-Groves (VCG) mechanism has been highlighted due to its adoption by Facebook ad auctions. Our research delves into its utility in the collab…
cs.LG2020★ 70 cited
Multi-Participant Multi-Class Vertical Federated Learning
Siwei Feng, Han Yu
Federated learning (FL) is a privacy-preserving paradigm for training collective machine learning models with locally stored data from multiple participants. Vertical federated lea…