1 citations · 1 across the 3 of their papers we have counts for
7 papers
MambaLSTM: A Spatio-Temporal Framework for Enhanced Traffic Accident Risk Prediction
Zhen Yu, Yachao Yuan, Zixiang Peng +2
In traffic accident risk prediction, most studies overlook the extra noise that could be incorporated when fusing temporal features into spatial features, and some models struggle…
HFL-FlowLLM: Large Language Models for Network Traffic Flow Classification in Heterogeneous Federated Learning
Jiazhuo Tian, Yachao Yuan
In modern communication networks driven by 5G and the Internet of Things (IoT), effective network traffic flow classification is crucial for Quality of Service (QoS) management and…
FedAPTA: Federated Multi-task Learning for Heterogeneous Devices with Adaptive Layer-wise Pruning and Task-aware Aggregation
Zhen Yu, Yachao Yuan, Jin Wang +2
Federated Learning (FL) has shown considerable promise in Machine Learning (ML) across numerous devices for privacy protection, efficient data utilization, and dynamic collaboratio…
Local Differential Privacy for Tensors in Distributed Computing Systems
Yachao Yuan, Xiao Tang, Yu Huang +2
Tensor-valued data, increasingly common in distributed big data applications like autonomous driving and smart healthcare, poses unique challenges for privacy protection due to its…
RoadFed: A Multimodal Federated Learning System for Improving Road Safety
Yachao Yuan, Zhen Yu, Yali Yuan +3
Internet of Things (IoTs) have been widely applied in Collaborative Intelligent Transportation Systems (C-ITS) for the prevention of road accidents. As one of the primary causes of…
AnomalyAID: Reliable Interpretation for Semi-supervised Network Anomaly Detection
Yachao Yuan, Yu Huang, Yingwen Wu +1
Semi-supervised Learning plays a crucial role in network anomaly detection applications, however, learning anomaly patterns with limited labeled samples is not easy. Additionally,…