42 citations · 50 across the 4 of their papers we have counts for
5 papers
FedModule: A Modular Federated Learning Framework
Chuyi Chen, Zhe Zhang, Yanchao Zhao
Federated learning (FL) has been widely adopted across various applications, such as healthcare, finance, and smart cities. However, as experimental scenarios become more complex,…
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
Ye Li, Yanchao Zhao, Chengcheng Zhu +1
Federated Learning (FL), a privacy-preserving decentralized machine learning framework, has been shown to be vulnerable to backdoor attacks. Current research primarily focuses on t…
Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction
Qiang Zhou, Jingjing Gu, Xinjiang Lu +4
Potential crowd flow prediction for new planned transportation sites is a fundamental task for urban planners and administrators. Intuitively, the potential crowd flow of the new c…
Exploiting Interpretable Patterns for Flow Prediction in Dockless Bike Sharing Systems
Jingjing Gu, Qiang Zhou, Jingyuan Yang +4
Unlike the traditional dock-based systems, dockless bike-sharing systems are more convenient for users in terms of flexibility. However, the flexibility of these dockless systems c…
DeepCount: Crowd Counting with WiFi via Deep Learning
Shangqing Liu, Yanchao Zhao, Fanggang Xue +2
Recently, the research of wireless sensing has achieved more intelligent results, and the intelligent sensing of human location and activity can be realized by means of WiFi device…