# BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning

@article{Ying2021BlueFogMD, title={BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning}, author={Bicheng Ying and Kun Yuan and Hanbin Hu and Yiming Chen and Wotao Yin}, journal={ArXiv}, year={2021}, volume={abs/2111.04287} }

Decentralized algorithm is a form of computation that achieves a global goal through local dynamics that relies on low-cost communication between directly-connected agents. On large-scale optimization tasks involving distributed datasets, decentralized algorithms have shown strong, sometimes superior, performance over distributed algorithms with a central node. Recently, developing decentralized algorithms for deep learning has attracted great attention. They are considered as low-communication…

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## 5 Citations

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