112 citations · 130 across the 7 of their papers we have counts for
7 papers
Owen Sampling Accelerates Contribution Estimation in Federated Learning
Hossein KhademSohi, Hadi Hemmati, Jiayu Zhou +1
Federated Learning (FL) aggregates information from multiple clients to train a shared global model without exposing raw data. Accurately estimating each client's contribution is e…
FedGreen: Carbon-aware Federated Learning with Model Size Adaptation
Ali Abbasi, Fan Dong, Xin Wang +3
Federated learning (FL) provides a promising collaborative framework to build a model from distributed clients, and this work investigates the carbon emission of the FL process. Cl…
Federated Learning Model Aggregation in Heterogenous Aerial and Space Networks
Fan Dong, Ali Abbasi, Henry Leung +3
Federated learning offers a promising approach under the constraints of networking and data privacy constraints in aerial and space networks (ASNs), utilizing large-scale private e…
FedLE: Federated Learning Client Selection with Lifespan Extension for Edge IoT Networks
Jiajun Wu, Steve Drew, Jiayu Zhou
Federated learning (FL) is a distributed and privacy-preserving learning framework for predictive modeling with massive data generated at the edge by Internet of Things (IoT) devic…
A Privacy-Preserving Hybrid Federated Learning Framework for Financial Crime Detection
Haobo Zhang, Junyuan Hong, Fan Dong +3
The recent decade witnessed a surge of increase in financial crimes across the public and private sectors, with an average cost of scams of $102m to financial institutions in 2022.…
Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey
Jiajun Wu, Steve Drew, Fan Dong +2
The ultra-low latency requirements of 5G/6G applications and privacy constraints call for distributed machine learning systems to be deployed at the edge. With its simple yet effec…
MDA: Availability-Aware Federated Learning Client Selection
Amin Eslami Abyane, Steve Drew, Hadi Hemmati
Recently, a new distributed learning scheme called Federated Learning (FL) has been introduced. FL is designed so that server never collects user-owned data meaning it is great at…