1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility
Xiaojin Zhang, Wenjie Li, Yiming Li +3
We propose a general learning framework for the protection mechanisms that protects privacy via distorting model parameters, which facilitates the trade-off between privacy and uti…
cs.LG2022
Vertical Semi-Federated Learning for Efficient Online Advertising
Wenjie Li, Shu-Tao Xia, Jiangke Fan +2
Traditional vertical federated learning schema suffers from two main issues: 1) restricted applicable scope to overlapped samples and 2) high system challenge of real-time federate…
cs.LG2022★ 1 cited
VFed-SSD: Towards Practical Vertical Federated Advertising
Wenjie Li, Qiaolin Xia, Junfeng Deng +5
As an emerging secure learning paradigm in lever-aging cross-agency private data, vertical federatedlearning (VFL) is expected to improve advertising models by enabling the joint l…