7 citations · 9 across the 5 of their papers we have counts for
3 papers · 1 filter
QuantFL: Sustainable Federated Learning for Edge IoT via Pre-Trained Model Quantisation
Charuka Herath, Yogachandran Rahulamathavan, Varuna De Silva +1
Federated Learning (FL) enables privacy-preserving intelligence on Internet of Things (IoT) devices but incurs a significant carbon footprint due to the high energy cost of frequen…
Enhancing Federated Learning Convergence with Dynamic Data Queue and Data Entropy-driven Participant Selection
Charuka Herath, Xiaolan Liu, Sangarapillai Lambotharan +1
Federated Learning (FL) is a decentralized approach for collaborative model training on edge devices. This distributed method of model training offers advantages in privacy, securi…
Recursive Euclidean Distance Based Robust Aggregation Technique For Federated Learning
Charuka Herath, Yogachandran Rahulamathavan, Xiaolan Liu
Federated learning has gained popularity as a solution to data availability and privacy challenges in machine learning. However, the aggregation process of local model updates to o…