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Federated learning (FL) is a popular framework for training an AI model using distributed mobile data in a wireless network.
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K. B. Letaief, W. Chen, Y. Shi, J. Zhang, and Y.-J. A. Zhang, “The roadmap to 6g: AI empowered wireless networks,” IEEE Commun. Mag
2019
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G. Zhu, Y. Wang, and K. Huang, “Broadband analog aggregation for low-latency federated edge learning,” IEEE Trans. Wireless Commun
2019
Cited alongside, same era.
H. H. Yang, Z. Liu, T. Q. Quek, and H. V. Poor, “Scheduling policies for federated learning in wireless networks,” IEEE Trans. Commun
2019
Cited alongside, same era.
S. Lin, Z. Zhou, Z. Zhang, X. Chen, and J. Zhang, “Edge intelligence in the making: Optimization, deep learning, and applications,” Synthesis Lectures on Learn., Netw., and Algorithms
2020
Cited alongside, same era.
M. M. Amiri and D. Gündüz, “Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air,” IEEE Trans. Signal Process
2020
Cited alongside, same era.
K. Yang, T. Jiang, Y. Shi, and Z. Ding, “Federated learning via over-the-air computation,” IEEE Trans. Wireless Commun
2020
J. Ren, Y. He, D. Wen, G. Yu, K. Huang, and D. Guo, “Scheduling in cellular federated edge learning with importance and channel awareness,” IEEE Trans. Wireless Commun
2020
Later among the works it cites.
W. Shi, S. Zhou, and Z. Niu, “Device scheduling with fast convergence for wireless federated learning,” in 2020 IEEE Int. Conf. Commun. (ICC)
2020
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Y. Du, S. Yang, and K. Huang, “High-dimensional stochastic gradient quantization for communication-efficient edge learning,” IEEE Trans. Signal Process
2020
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D. Wen, M. Bennis, and K. Huang, “Joint parameter-and-bandwidth allocation for improving the efficiency of partitioned edge learning,” IEEE Trans. Wireless Commun
2020
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D. Wen, K.-J. Jeon, M. Bennis, and K. Huang, “Adaptive subcarrier, parameter, and power allocation for partitioned edge learning over broadband channels,” to appear in IEEE Trans. Wireless Commun
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Cited alongside, same era.
M. Chen, Z. Yang, W. Saad, C. Yin, H. V. Poor, and S. Cui, “A joint learning and communications framework for federated learning over wireless networks,” IEEE Trans. Wireless Commun
2020
Cited alongside, same era.
2020
Later among the works it cites.