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Jun, 2018
误差补偿量化 SGD 及其在大规模分布式优化中的应用
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
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Jiaxiang Wu, Weidong Huang, Junzhou Huang, Tong Zhang
TL;DR
本文提出了误差补偿量化随机梯度下降算法以优化数据分布式学习中的性能瓶颈，并对其收敛性行为进行了理论分析，同时通过实验证明了该算法在梯度压缩方面具有较大优势。
Abstract
large-scale distributed optimization
is of great importance in various applications. For data-parallel based distributed learning, the inter-node gradient communication often becomes the
performance bottleneck
. I
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