5 papers
Agentic AI as a Network Control-Plane Intelligence Layer for Federated Learning over 6G
Loc X. Nguyen, Ji Su Yoon, Huy Q. Le +6
The shift toward user-customized on-device learning places new demands on wireless systems: models must be trained on diverse, distributed data while meeting strict latency, bandwi…
Robust Federated Learning on Edge Devices with Domain Heterogeneity
Huy Q. Le, Latif U. Khan, Choong Seon Hong
Federated Learning (FL) allows collaborative training while ensuring data privacy across distributed edge devices, making it a popular solution for privacy-sensitive applications.…
Mitigating Domain Shift in Federated Learning via Intra- and Inter-Domain Prototypes
Huy Q. Le, Ye Lin Tun, Yu Qiao +4
Federated Learning (FL) has emerged as a decentralized machine learning technique, allowing clients to train a global model collaboratively without sharing private data. However, m…
CLIP-PING: Boosting Lightweight Vision-Language Models with Proximus Intrinsic Neighbors Guidance
Chu Myaet Thwal, Ye Lin Tun, Minh N. H. Nguyen +2
Beyond the success of Contrastive Language-Image Pre-training (CLIP), recent trends mark a shift toward exploring the applicability of lightweight vision-language models for resour…
Towards Satellite Non-IID Imagery: A Spectral Clustering-Assisted Federated Learning Approach
Luyao Zou, Yu Min Park, Chu Myaet Thwal +3
Low Earth orbit (LEO) satellites are capable of gathering abundant Earth observation data (EOD) to enable different Internet of Things (IoT) applications. However, to accomplish an…