2 citations · 4 across the 4 of their papers we have counts for
4 papers
DAG-ACFL: Asynchronous Clustered Federated Learning based on DAG-DLT
Xiaofeng Xue, Haokun Mao, Qiong Li
Federated learning (FL) aims to collaboratively train a global model while ensuring client data privacy. However, FL faces challenges from the non-IID data distribution among clien…
An Energy Optimized Specializing DAG Federated Learning based on Event Triggered Communication
Xiaofeng Xue, Haokun Mao, Qiong Li +1
Specializing Directed Acyclic Graph Federated Learning(SDAGFL) is a new federated learning framework which updates model from the devices with similar data distribution through Dir…
High-speed Privacy Amplification Scheme using GMP in Quantum Key Distribution
Bingze Yan, Haokun Mao, Xiaofeng Xue +1
Privacy amplification (PA) is the art of distilling a highly secret key from a partially secure string by public discussion. It is a vital procedure in quantum key distribution (QK…
High-speed Implementation of FFT-based Privacy Amplification on FPGA in Quantum Key Distribution
Qiong Li, Bing-Ze Yan, Hao-Kun Mao +1
Privacy amplification (PA) is a vital procedure in quantum key distribution (QKD) to generate the secret key that the eavesdropper has only negligible information from the identica…