2 citations · 3 across the 25 of their papers we have counts for
4 papers · 1 filter
Decentralized Federated Learning With Energy Harvesting Devices
Kai Zhang, Xuanyu Cao, Khaled B. Letaief
Decentralized federated learning (DFL) enables edge devices to collaboratively train models through local training and fully decentralized device-to-device (D2D) model exchanges. H…
Communication-Efficient Multi-Modal Edge Inference via Uncertainty-Aware Distributed Learning
Hang Zhao, Hongru Li, Dongfang Xu +2
Semantic communication is emerging as a key enabler for distributed edge intelligence due to its capability to convey task-relevant meaning. However, achieving communication-effici…
Siamese Machine Unlearning with Knowledge Vaporization and Concentration
Songjie Xie, Hengtao He, Shenghui Song +2
In response to the practical demands of the ``right to be forgotten" and the removal of undesired data, machine unlearning emerges as an essential technique to remove the learned k…
Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks
Tianqu Kang, Zixin Wang, Hengtao He +3
Fine-tuning large pre-trained foundation models (FMs) on distributed edge devices presents considerable computational and privacy challenges. Federated fine-tuning (FedFT) mitigate…