112 citations · 116 across the 10 of their papers we have counts for
5 papers · 1 filter
SPEAR: Soft Prompt Enhanced Anomaly Recognition for Time Series Data
Hanzhe Wei, Jiajun Wu, Jialin Yang +2
Time series anomaly detection plays a crucial role in a wide range of fields, such as healthcare and internet traffic monitoring. The emergence of large language models (LLMs) offe…
Navigating High-Degree Heterogeneity: Federated Learning in Aerial and Space Networks
Fan Dong, Henry Leung, Steve Drew
Federated learning offers a compelling solution to the challenges of networking and data privacy within aerial and space networks by utilizing vast private edge data and computing…
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…
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…