Compressing Key-Value Pairs for Efficient Distributed SGD Algotithm-Reference-Cited by-同舟云学术

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Compressing Key-Value Pairs for Efficient Distributed SGD Algotithm

Published:2023-10-20 Issue: Volume:31 Page:1-10
ISSN:
Container-title:2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
language:
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Author:

Ruan Yazhou¹,Zheng Xuexin²,Zhao Weiwei³,Hu Changhui⁴

Affiliation:

1. School of Cyberspace Security Hainan University,Key Laboratory of Internet Information Retrieval of Hainan Province,Hainan,China

2. China Academy of Information and Communications Technology,Beijing,P.R.China

3. School of Science Hainan University,Key Laboratory of Internet Information Retrieval of Hainan Province,Haikou,P.R.China

4. Hainan University Key Laboratory of Internet Information Retrieval of Hainan Province,School of Cyberspace Security,Haikou,P.R.China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391855/10391862/10393360.pdf?arnumber=10393360

Reference20 articles.

1. Communication compression for decentralized training;Tang;Advances in Neural Information Processing Systems,2018

2. Combining multiple evidence for video classification

3. The zipml framework for training models with end-to-end low precision: The cans, the cannots, and a little bit of deep learning;Zhang,2016

4. Communication-Efficient Federated Learning via Quantized Compressed Sensing

5. Gradient sparsification for communication-efficient distributed optimization;Wangni;Advances in Neural Information Processing Systems,2018

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