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5 ene 2017 año - Deep Learning with Low Precision by Half-wave Gaussian Quantization (HWGQ)

Descripción:

本文主要讨论了在低位宽量化的近似梯度训练中，梯度消失的问题，通过设计新的量化函数(sign/Q)和激活函数来保证梯度不消失，以实现量化模型的收敛。有趣的是，仅通过对relu函数的剪切或者log-tail变换，模型的性能得到了显著提升。这或许就是特征的影响

Añadido al timeline:

Quantization timeline

By龚成
29 mar 2020

fecha:

5 ene 2017 año
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