12 citations · 20 across the 6 of their papers we have counts for
3 papers · 1 filter
An Empirical Study of Federated Learning on IoT-Edge Devices: Resource Allocation and Heterogeneity
Kok-Seng Wong, Manh Nguyen-Duc, Khiem Le-Huy +3
Nowadays, billions of phones, IoT and edge devices around the world generate data continuously, enabling many Machine Learning (ML)-based products and applications. However, due to…
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions
Thuy Dung Nguyen, Tuan Nguyen, Phi Le Nguyen +3
Federated learning (FL) is a machine learning (ML) approach that allows the use of distributed data without compromising personal privacy. However, the heterogeneous distribution o…
Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning
Van-Tuan Tran, Huy-Hieu Pham, Kok-Seng Wong
Federated learning (FL) is recently surging as a promising decentralized deep learning (DL) framework that enables DL-based approaches trained collaboratively across clients withou…