1 code implementation • 16 Oct 2021 • Yan Shen, Jian Du, Han Zhao, Benyu Zhang, Zhanghexuan Ji, Mingchen Gao
Federated adversary domain adaptation is a unique distributed minimax training task due to the prevalence of label imbalance among clients, with each client only seeing a subset of the classes of labels required to train a global model.
no code implementations • 1 Jan 2021 • Yan Shen, Jian Du, Chunwei Ma, Mingchen Gao, Benyu Zhang
Our introduced SGLD oracle would lower generalization errors in local node's parameter learning and provide local node DP protections.
no code implementations • 6 Nov 2020 • Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang
Specifically, to solve the data Non-IID problem, we first propose a separated-federated GNN learning model, which decouples the training of GNN into two parts: the message passing part that is done by clients separately, and the loss computing part that is learnt by clients federally.
no code implementations • 18 May 2020 • Wenjing Fang, Derun Zhao, Jin Tan, Chaochao Chen, Chaofan Yu, Li Wang, Lei Wang, Jun Zhou, Benyu Zhang
Privacy-preserving machine learning has drawn increasingly attention recently, especially with kinds of privacy regulations come into force.