12 citations · 30 across the 5 of their papers we have counts for
5 papers
Q-learning-based Opportunistic Communication for Real-time Mobile Air Quality Monitoring Systems
Trung Thanh Nguyen, Truong Thao Nguyen, Dinh Tuan Anh Nguyen +2
We focus on real-time air quality monitoring systems that rely on devices installed on automobiles in this research. We investigate an opportunistic communication model in which de…
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…
FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Collaborative Training
Quan Nguyen, Hieu H. Pham, Kok-Seng Wong +3
We introduce FedDCT, a novel distributed learning paradigm that enables the usage of large, high-performance CNNs on resource-limited edge devices. As opposed to traditional FL app…
An Oracle for Guiding Large-Scale Model/Hybrid Parallel Training of Convolutional Neural Networks
Albert Njoroge Kahira, Truong Thao Nguyen, Leonardo Bautista Gomez +3
Deep Neural Network (DNN) frameworks use distributed training to enable faster time to convergence and alleviate memory capacity limitations when training large models and/or using…
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA
Mohamed Wahib, Haoyu Zhang, Truong Thao Nguyen +5
The dedicated memory of hardware accelerators can be insufficient to store all weights and/or intermediate states of large deep learning models. Although model parallelism is a via…