Guest Editorial Special Issue on Distributed Learning Over Wireless Edge Networks-Part II

被引:1
|
作者
Chen, Mingzhe [1 ]
Gunduz, Deniz [2 ]
Huang, Kaibin [3 ]
Saad, Walid [4 ]
Bennis, Mehdi [5 ]
Feljan, Aneta Vulgarakis [6 ]
Poor, H. Vincent [1 ]
机构
[1] Princeton Univ, Dept Elect & Comp Engn, Princeton, NJ 08544 USA
[2] Imperial Coll London, Dept Elect & Elect Engn, London SW7 2AZ, England
[3] Univ Hong Kong, Dept Elect & Elect Engn, Hong Kong, Peoples R China
[4] Virginia Tech, Bradley Dept Elect & Comp Engn, Wireless VT, Blacksburg, VA 24060 USA
[5] Univ Oulu, Dept Commun Engn, Oulu 90014, Finland
[6] Ericsson Res, S-16483 Stockholm, Sweden
关键词
D O I
10.1109/JSAC.2021.3118515
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This is Part II of a double-part special issue on distributed learning over wireless edge networks. This two-part special issue features papers dealing with two main research challenges: optimization of wireless network performance for efficient implementation of distributed learning in wireless networks, and distributed learning for solving communication problems and optimizing network performance. The accepted papers in this special issue have been grouped into three topics: 1) network optimization for federated learning (FL), 2) network optimization for other distributed learning methods, and 3) distributed reinforcement learning (RL) for wireless network optimization. In Part I (vol. 39, no. 12, Dec. 2021), the focus is on the first cluster (network optimization for FL). The focus of Part II is on the second and third clusters (network optimization for other distributed learning methods and RL for wireless network optimization). The readers are referred to Part I for an overview paper [A1] by the team of guest editors where a comprehensive study of how distributed learning can be efficiently deployed over wireless edge networks is provided. The contributions made by the papers in Part II are summarized as follows.
引用
收藏
页码:445 / 448
页数:4
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