activity
20202026
most citedAn Efficient and Multi-private Key Secure Aggregation for Federated Learning

3 citations · 6 across the 8 of their papers we have counts for

collaborators
Showing 2025Show all

2 papers · 1 filter

cs.CR2025

Efficient Byzantine-Robust Privacy-Preserving Federated Learning via Dimension Compression

Xian Qin, Xue Yang, Xiaohu Tang

Federated Learning (FL) allows collaborative model training across distributed clients without sharing raw data, thus preserving privacy. However, the system remains vulnerable to…

cs.LG2025

Orthogonal Soft Pruning for Efficient Class Unlearning

Qinghui Gong, Xue Yang, Xiaohu Tang

Efficient and controllable data unlearning in federated learning remains challenging, due to the trade-off between forgetting and retention performance. Especially under non-indepe…