activity
20162024
most citedDistributed Traffic Synthesis and Classification in Edge Networks: A Federated Self-supervised Learning Approach

48 citations · 130 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2024

CNN-FL for Biotechnology Industry Empowered by Internet-of-BioNano Things and Digital Twins

Mohammad, Jamshidi, Dinh Thai Hoang +1

Digital twins (DTs) are revolutionizing the biotechnology industry by enabling sophisticated digital representations of biological assets, microorganisms, drug development processe…

cs.CR20231 cited

MetaShard: A Novel Sharding Blockchain Platform for Metaverse Applications

Cong T. Nguyen, Dinh Thai Hoang, Diep N. Nguyen +3

Due to its security, transparency, and flexibility in verifying virtual assets, blockchain has been identified as one of the key technologies for Metaverse. Unfortunately, blockcha…

cs.NI20231 cited

Dynamic Resource Allocation for Metaverse Applications with Deep Reinforcement Learning

Nam H. Chu, Diep N. Nguyen, Dinh Thai Hoang +4

This work proposes a novel framework to dynamically and effectively manage and allocate different types of resources for Metaverse applications, which are forecasted to demand mass…

cs.LG20231 cited

Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework

Van-Dinh Nguyen, Thang X. Vu, Nhan Thanh Nguyen +6

To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open R…

cs.LG202348 cited

Distributed Traffic Synthesis and Classification in Edge Networks: A Federated Self-supervised Learning Approach

Yong Xiao, Rong Xia, Yingyu Li +5

With the rising demand for wireless services and increased awareness of the need for data protection, existing network traffic analysis and management architectures are facing unpr…

cs.LG202337 cited

Time-sensitive Learning for Heterogeneous Federated Edge Intelligence

Yong Xiao, Xiaohan Zhang, Guangming Shi +3

Real-time machine learning has recently attracted significant interest due to its potential to support instantaneous learning, adaptation, and decision making in a wide range of ap…