39 citations · 40 across the 7 of their papers we have counts for
8 papers
Final Report on the Measurement of the Positive Muon Anomalous Magnetic Moment at Fermilab to 127 ppb
2 Collaboration, D. P. Aguillard, T. Albahri +192
This report details the final measurement of the muon magnetic anomaly, , by the Muon experiment at Fermi National Accelerator Laboratory (FNAL), using positiv…
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…
Microsecond Federated SVD on Grassmann Manifold for Real-time IoT Intrusion Detection
Tung-Anh Nguyen, Van-Phuc Bui, Shashi Raj Pandey +3
This paper introduces FedSVD, a novel unsupervised federated learning framework for real-time anomaly detection in IoT networks. By leveraging Singular Value Decomposition (SVD) an…
Distributionally Robust Wireless Semantic Communication with Large AI Models
Long Tan Le, Senura Hansaja Wanasekara, Zerun Niu +7
Semantic communication (SemCom) has emerged as a promising paradigm for 6G wireless systems by transmitting task-relevant information rather than raw bits, yet existing approaches…
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection
Long Tan Le, Tung-Anh Nguyen, Han Shu +3
The proliferation of edge devices has dramatically increased the generation of multivariate time-series (MVTS) data, essential for applications from healthcare to smart cities. Suc…
Federated PCA on Grassmann Manifold for IoT Anomaly Detection
Tung-Anh Nguyen, Long Tan Le, Tuan Dung Nguyen +4
With the proliferation of the Internet of Things (IoT) and the rising interconnectedness of devices, network security faces significant challenges, especially from anomalous activi…
REPO: mplicit Reward Pairwise Difference based Empirical Preference Optimization
Long Tan Le, Han Shu, Tung-Anh Nguyen +2
While astonishingly capable, large Language Models (LLM) can sometimes produce outputs that deviate from human expectations. Such deviations necessitate an alignment phase to preve…
Federated Deep Equilibrium Learning: Harnessing Compact Global Representations to Enhance Personalization
Long Tan Le, Tuan Dung Nguyen, Tung-Anh Nguyen +4
Federated Learning (FL) has emerged as a groundbreaking distributed learning paradigm enabling clients to train a global model collaboratively without exchanging data. Despite enha…