39 citations · 40 across the 7 of their papers we have counts for
8 papers
GoodSpeed: Optimizing Fair Goodput with Adaptive Speculative Decoding in Distributed Edge Inference
Phuong Tran, Tzu-Hao Liu, Long Tan Le +6
Large language models (LLMs) have revolutionized natural language processing, yet their high computational demands pose significant challenges for real-time inference, especially i…
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…
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks
Tung-Anh Nguyen, Jiayu He, Long Tan Le +2
In the era of Internet of Things (IoT), network-wide anomaly detection is a crucial part of monitoring IoT networks due to the inherent security vulnerabilities of most IoT devices…
On the Generalization of Wasserstein Robust Federated Learning
Tung-Anh Nguyen, Tuan Dung Nguyen, Long Tan Le +2
In federated learning, participating clients typically possess non-i.i.d. data, posing a significant challenge to generalization to unseen distributions. To address this, we propos…