6 citations · 11 across the 5 of their papers we have counts for
4 papers · 1 filter
Fairness-aware Agnostic Federated Learning
Wei Du, Depeng Xu, Xintao Wu +1
Federated learning is an emerging framework that builds centralized machine learning models with training data distributed across multiple devices. Most of the previous works about…
PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing
Ang Li, Wei Du, Qinghua Li
Camera is a standard on-board sensor of modern mobile phones. It makes photo taking popular due to its convenience and high resolution. However, when users take a photo of a scener…
Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy
Depeng Xu, Wei Du, Xintao Wu
When we enforce differential privacy in machine learning, the utility-privacy trade-off is different w.r.t. each group. Gradient clipping and random noise addition disproportionate…
Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach
Zeyue Xue, Shuang Luo, Chao Wu +3
Peer-to-peer knowledge transfer in distributed environments has emerged as a promising method since it could accelerate learning and improve team-wide performance without relying o…