Learning low-precision neural networks without Straight-Through Estimator(STE)

4 Mar 2019 Zhi-Gang Liu Matthew Mattina

The Straight-Through Estimator (STE) is widely used for back-propagating gradients through the quantization function, but the STE technique lacks a complete theoretical understanding. We propose an alternative methodology called alpha-blending (AB), which quantizes neural networks to low-precision using stochastic gradient descent (SGD)... (read more)

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