most citedFedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023

FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection

Thuy Dung Nguyen, Anh Duy Nguyen, Kok-Seng Wong +4

Federated learning (FL) enables multiple clients to train a model without compromising sensitive data. The decentralized nature of FL makes it susceptible to adversarial attacks, e…

cs.CV2023

Ensemble Learning of Myocardial Displacements for Myocardial Infarction Detection in Echocardiography

Nguyen Tuan, Phi Nguyen, Dai Tran +10

Early detection and localization of myocardial infarction (MI) can reduce the severity of cardiac damage through timely treatment interventions. In recent years, deep learning tech…

cs.LG20231 cited

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…

cs.CV2022

Image-based Contextual Pill Recognition with Medical Knowledge Graph Assistance

Anh Duy Nguyen, Thuy Dung Nguyen, Huy Hieu Pham +2

Identifying pills given their captured images under various conditions and backgrounds has been becoming more and more essential. Several efforts have been devoted to utilizing the…

cs.LG20222 cited

FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning

Nang Hung Nguyen, Phi Le Nguyen, Duc Long Nguyen +4

The uneven distribution of local data across different edge devices (clients) results in slow model training and accuracy reduction in federated learning. Naive federated learning…