Kaibin Huang

Distributed Learning in Wireless Networks: Recent Progress and Future Challenges

2021 · arXiv (Cornell University)

The next-generation of wireless networks will enable many machine learning (ML) tools and applications to efficiently analyze various types of data collected by edge devices for inference, autonomy, and decision making purposes. However, due to …

Efficient Parallel Split Learning Over Resource-Constrained Wireless Edge Networks

2024 · IEEE Transactions on Mobile Computing

The increasingly deeper neural networks hinder the democratization of privacy-enhancing distributed learning, such as federated learning (FL), to resource-constrained devices. To overcome this challenge, in this paper, we advocate the integration of edge computing paradigm …