1 code implementation • 21 Nov 2023 • Shu Zheng, Tiandi Ye, Xiang Li, Ming Gao
We theoretically show that the consensus mechanism can guarantee the convergence of the global objective.
no code implementations • 29 Jul 2023 • Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao
To address this challenge, we extend the adaptive risk minimization technique into the unsupervised personalized federated learning setting and propose our method, FedTTA.
1 code implementation • 29 Jul 2023 • Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao
The resistance of pFL methods with parameter decoupling is attributed to the heterogeneous classifiers between malicious clients and benign counterparts.
no code implementations • 29 Jan 2023 • Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
In this paper, to comprehensively enhance the performance of generative graph SSL against other GCL models on both unsupervised and supervised learning tasks, we propose the SeeGera model, which is based on the family of self-supervised variational graph auto-encoder (VGAE).
no code implementations • 2 Nov 2021 • Jamie Cui, Cen Chen, Tiandi Ye, Li Wang
Existing work fails to provide a loss-less scheme, or has impractical efficiency.