Applications in AIoT: Federated Distributed Learning for Edge IoT

Author:

Lin Shih-Chun,Chang Tsung-Hui,Jorswieck Eduard,Lin Pin-Hsun

Publisher

Springer Nature Singapore

Reference34 articles.

1. Wang X, Han Y, Wang C, Zhao Q, Chen X, Chen M (2019) In-edge ai: intelligentizing mobile edge computing, caching and communication by federated learning. IEEE Netw 33(5):156–165

2. Zhu G, Liu D, Du Y, You C, Zhang J, Huang K (2020) Toward an intelligent edge: wireless communication meets machine learning. IEEE Commun Mag 58(1):19–25

3. Lim WYB, Luong NC, Hoang DT, Jiao Y, Liang Y-C, Yang Q, Niyato D, Miao C (2020) Federated learning in mobile edge networks: a comprehensive survey. IEEE Commun Surv Tuts 22(3):2031–2063

4. McMahan B, Moore E, Ramage D, Hampson S, y Arcas BA (2017) Communication-efficient learning of deep networks from decentralized data. In: Artificial intelligence and statistics, pp 1273–1282

5. Wang J, Liu Q, Liang H, Joshi G, Poor HV (2020) Tackling the objective inconsistency problem in heterogeneous federated optimization. arXiv:2007.07481

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