3 papers
eess.SY2025
Robust Indoor Localization via Conformal Methods and Variational Bayesian Adaptive Filtering
Zhiyi Zhou, Dongzhuo Liu, Songtao Guo +1
Indoor localization is critical for IoT applications, yet challenges such as non-Gaussian noise, environmental interference, and measurement outliers hinder the robustness of tradi…
cs.AI2024
FedPAW: Federated Learning with Personalized Aggregation Weights for Urban Vehicle Speed Prediction
Yuepeng He, Pengzhan Zhou, Yijun Zhai +4
Vehicle speed prediction is crucial for intelligent transportation systems, promoting more reliable autonomous driving by accurately predicting future vehicle conditions. Due to va…
cs.DC2024
FedRAV: Hierarchically Federated Region-Learning for Traffic Object Classification of Autonomous Vehicles
Yijun Zhai, Pengzhan Zhou, Yuepeng He +5
The emerging federated learning enables distributed autonomous vehicles to train equipped deep learning models collaboratively without exposing their raw data, providing great pote…