237 citations · 362 across the 22 of their papers we have counts for
4 papers · 1 filter
Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning
Rakpong Kaewpuang, Minrui Xu, Dusit Niyato +3
Increasing privacy and security concerns in intelligence-native 6G networks require quantum key distribution-secured federated learning (QKD-FL), in which data owners connected via…
FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning
Yuanyuan Chen, Zichen Chen, Pengcheng Wu +1
Large-scale neural networks possess considerable expressive power. They are well-suited for complex learning tasks in industrial applications. However, large-scale models pose sign…
Federated Graph Neural Networks: Overview, Techniques and Challenges
Rui Liu, Pengwei Xing, Zichao Deng +3
With its capability to deal with graph data, which is widely found in practical applications, graph neural networks (GNNs) have attracted significant research attention in recent y…
Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training
Shenglai Zeng, Zonghang Li, Hongfang Yu +4
Federated learning (FL) is a rapidly growing privacy-preserving collaborative machine learning paradigm. In practical FL applications, local data from each data silo reflect local…