1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs
Tianyi Zhao, Hui Hu, Lu Cheng
Graph Neural Networks (GNNs) are powerful tools for learning representations on graphs, such as social networks. However, their vulnerability to privacy inference attacks restricts…
cs.LG2019★ 1 cited
A Distributed Fair Machine Learning Framework with Private Demographic Data Protection
Hui Hu, Yijun Liu, Zhen Wang +1
Fair machine learning has become a significant research topic with broad societal impact. However, most fair learning methods require direct access to personal demographic data, wh…
cs.LG2019
Fair Kernel Regression via Fair Feature Embedding in Kernel Space
Austin Okray, Hui Hu, Chao Lan
In recent years, there have been significant efforts on mitigating unethical demographic biases in machine learning methods. However, very little is done for kernel methods. In thi…