11 citations · 13 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy
Yifan Shi, Kang Wei, Li Shen +4
To defend the inference attacks and mitigate the sensitive information leakages in Federated Learning (FL), client-level Differentially Private FL (DPFL) is the de-facto standard f…
cs.LG2023★ 11 cited
Improving the Model Consistency of Decentralized Federated Learning
Yifan Shi, Li Shen, Kang Wei +4
To mitigate the privacy leakages and communication burdens of Federated Learning (FL), decentralized FL (DFL) discards the central server and each client only communicates with its…
cs.LG2023★ 1 cited
SaFormer: A Conditional Sequence Modeling Approach to Offline Safe Reinforcement Learning
Qin Zhang, Linrui Zhang, Haoran Xu +6
Offline safe RL is of great practical relevance for deploying agents in real-world applications. However, acquiring constraint-satisfying policies from the fixed dataset is non-tri…