DoReFa-Net: Training low bitwidth convolutional neural networks with low bitwidth gradients
arXiv preprint arXiv:1606.06160, 2016.
We propose DoReFa-Net, a method to train convolutional neural networks that have low bitwidth weights and activations using low bitwidth parameter gradients. In particular, during backward pass, parameter gradients are stochastically quantized to low bitwidth numbers before being propagated to convolutional layers. As convolutions during ...More
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