Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks

no code implementations • 18 Jan 2024 • Tan Chen, Jintao Yan, Yuxuan Sun, Sheng Zhou, Deniz Gündüz, Zhisheng Niu

Hierarchical federated learning (HFL) enables distributed training of models across multiple devices with the help of several edge servers and a cloud edge server in a privacy-preserving manner.

Federated Learning Privacy Preserving

Data-Heterogeneous Hierarchical Federated Learning with Mobility

no code implementations • 19 Jun 2023 • Tan Chen, Jintao Yan, Yuxuan Sun, Sheng Zhou, Deniz Gunduz, Zhisheng Niu

Federated learning enables distributed training of machine learning (ML) models across multiple devices in a privacy-preserving manner.

Federated Learning Privacy Preserving

CRT-Net: A Generalized and Scalable Framework for the Computer-Aided Diagnosis of Electrocardiogram Signals

no code implementations • 28 May 2021 • Jingyi Liu, Zhongyu Li, Xiayue Fan, Jintao Yan, Bolin Li, Xuemeng Hu, Qing Xia, Yue Wu

Subsequently, a novel deep neural network, namely CRT-Net, is designed for the fine-grained and comprehensive representation and recognition of 1-D ECG signals.