Communication and Energy Efficient Decentralized Learning Over D2D Networks-Reference-Cited by-同舟云学术

Communication and Energy Efficient Decentralized Learning Over D2D Networks

Author:

Liu Shengli¹^ORCID,Yu Guanding²^ORCID,Wen Dingzhu¹^ORCID,Chen Xianfu³^ORCID,Bennis Mehdi⁴^ORCID,Chen Hongyang⁵^ORCID

Affiliation:

1. School of Information and Electrical Engineering, Hangzhou City University, Hangzhou, China

2. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

3. VTT Technical Research Centre of Finland, Oulu, Finland

4. Centre for Wireless Communication, University of Oulu, Oulu, Finland

5. Research Center for Graph Computing, Zhejiang Lab, Hangzhou, China

Funder

National Key Research and Development Program of China

Shanghai Sailing Program

Zhejiang Lab Open Program

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Link

Reference49 articles.

2. Federated optimization: Distributed machine learning for on-device intelligence;Konecný;arXiv:1610.02527,2016

3. Can decentralized algorithms outperform centralized algorithms? A case study for decentralized parallel stochastic gradient descent;Lian

4. Collaborative deep learning in fixed topology networks;Jiang

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