Author

Brad Campbell

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Open access Oct 2026

H-FedSN: personalized sparse networks for efficient and accurate hierarchical federated learning for IoT applications

With the rapid development of the Internet of Things (IoT), federated learning (FL) has gained increasing attention for its privacy-preserving use of distributed data. However, conventional two-tier FL architectures are poorly suited to the hierarchical and heterogeneous nature of real-world IoT systems. Hierarchical...

Jie-Chao Gao, Yuan-Gang Li, Jie Wang et al. · npj Artificial Intelligence · 0 citations

#artificial intelligence Preprint Sep 2026

PrivateHub: Contrastive Diffusion Model for Private Sensor-Intensive Environment Data Generation

This work introduces Privatehub, which uses contrastive learning within a diffusion model to generate synthetic multi-sensor streams that keep non-private applications detectable while concealing private ones in sensor-intensive environments.

Jie-Chao Gao, Yuan-Dong Pan, Jie Wang et al. · 0 citations

#machine learning Dec 2024

H-FedSN: Personalized Sparse Networks for Efficient and Accurate Hierarchical Federated Learning for IoT Applications

Experiments show that H-FedSN reduces communication costs by up to 477 times compared to baseline methods while maintaining high accuracy, making it well-suited for hierarchical FL in IoT deployments.

Jiechao Gao, Yuangang Li, Jie Wang et al. · arXiv.org · 0 citations