74 citations · 101 across the 3 of their papers we have counts for
3 papers
cs.GT2022★ 9 cited
Online Auction-Based Incentive Mechanism Design for Horizontal Federated Learning with Budget Constraint
Jingwen Zhang, Yuezhou Wu, Rong Pan
Federated learning makes it possible for all parties with data isolation to train the model collaboratively and efficiently while satisfying privacy protection. To obtain a high-qu…
cs.AI2022★ 18 cited
Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement
Jingwen Zhang, Yuezhou Wu, Rong Pan
Federated learning trains models across devices with distributed data, while protecting the privacy and obtaining a model similar to that of centralized ML. A large number of worke…
cs.LG2021★ 74 cited
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Yuezhou Wu, Yan Kang, Jiahuan Luo +2
Federated learning (FL) aims to protect data privacy by enabling clients to build machine learning models collaboratively without sharing their private data. Recent works demonstra…