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README.rst

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For any questions or issues, please contact the development team at `guozh29@mail2.sysu.edu.cn`.
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[1] L. You, S. Liu, B. Zuo, C. Yuen*, D. Niyato, H. V. Poor,Federated and Asynchronized Learning for Autonomous and Intelligent Things, IEEE Network Magazine, 2023.
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[1] L. You, S. Liu, B. Zuo, C. Yuen*, D. Niyato, H. V. Poor,"Federated and Asynchronized Learning for Autonomous and Intelligent Things", IEEE Network Magazine, 2023.
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[2] L. You, S. Liu, T. Wang, B. Zuo, Y. Chang, C. Yuen*,AiFed: An Adaptive and Integrated Mechanism for Asynchronous Federated Data Mining, IEEE Transactions on Knowledge and Data Engineering, 2023.
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[2] L. You, S. Liu, T. Wang, B. Zuo, Y. Chang, C. Yuen*,"AiFed: An Adaptive and Integrated Mechanism for Asynchronous Federated Data Mining", IEEE Transactions on Knowledge and Data Engineering, 2023.
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[3] L. You, Z. Guo, B. Zuo, Y. Chang*, C. Yuen,SLMFed: A Stage-based and Layer-wise Mechanism for Incremental Federated Learning to Assist Dynamic and Ubiquitous IoT, IEEE Internet of Things Journal, 2024.
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[3] L. You, Z. Guo, B. Zuo, Y. Chang*, C. Yuen,"SLMFed: A Stage-based and Layer-wise Mechanism for Incremental Federated Learning to Assist Dynamic and Ubiquitous IoT", IEEE Internet of Things Journal, 2024.
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[4] L. You, S. Liu, Y. Chang, C. Yuen*, “A triple-step asynchronous federated learning mechanism for client activation, interaction optimization, and aggregation enhancement”, IEEE Internet of Things Journal, 2022.
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[4] L. You, S. Liu, Y. Chang, C. Yuen*,"A triple-step asynchronous federated learning mechanism for client activation, interaction optimization, and aggregation enhancement", IEEE Internet of Things Journal, 2022.
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[5] S. Liu, L. You*, R. Zhu, B. Liu, R. Liu, Y. Han, C. Yuen,"AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection", IEEE Transactions on Intelligent Transportation Systems, 2024.

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