2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Privacy-Preserving Orthogonal Aggregation for Guaranteeing Gender Fairness in Federated Recommendation
Siqing Zhang, Yuchen Ding, Wei Tang +3
Under stringent privacy constraints, whether federated recommendation systems can achieve group fairness remains an inadequately explored question. Taking gender fairness as a repr…
cs.CR2023★ 2 cited
AHSecAgg and TSKG: Lightweight Secure Aggregation for Federated Learning Without Compromise
Siqing Zhang, Yong Liao, Pengyuan Zhou
Leveraging federated learning (FL) to enable cross-domain privacy-sensitive data mining represents a vital breakthrough to accomplish privacy-preserving learning. However, attacker…
cs.CR2023
λ-SecAgg: Partial Vector Freezing for Lightweight Secure Aggregation in Federated Learning
Siqing Zhang, Yong Liao, Pengyuan Zhou
Secure aggregation of user update vectors (e.g. gradients) has become a critical issue in the field of federated learning. Many Secure Aggregation Protocols (SAPs) face exorbitant…