Label driven knowledge distillation for federated learning with non-iid data

[PDF] arxiv.org

Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Survey

TH Vu, SK Jagatheesaperumal, MD Nguyen… - arXiv preprint arXiv …, 2024 - arxiv.org
The success of Artificial Intelligence (AI) in multiple disciplines and vertical domains in
recent years has promoted the evolution of mobile networking and the future Internet toward …
被引用次数：6 相关文章 所有 2 个版本
[PDF] arxiv.org

Sample-Driven Federated Learning for Energy-Efficient and Real-Time IoT Sensing

MN Luu, MD Nguyen, E Bedeer, VD Nguyen… - arXiv preprint arXiv …, 2023 - arxiv.org
In the domain of Federated Learning (FL) systems, recent cutting-edge methods heavily rely
on ideal conditions convergence analysis. Specifically, these approaches assume that the …
被引用次数：2 相关文章 所有 2 个版本

An optimized federated learning method based on soft label grouping for heterogeneous IoT

Y Yang, Y Luo, G Zhu - Cluster Computing, 2024 - Springer
Abstract In the Internet of Things (IoT), a large number of devices generate data. Federated
learning can take advantage of the distributional nature of these devices to parallelize model …
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