Reviews: Backprop with Approximate Activations for Memory-efficient Network Training

I haven't seen papers that propose to do a simple uniform quantization in the preactivations just to save memory during training. But I could be over looking some of the network quantization literature. It shows that the proposed method is able to save memory while maintaining the same accuracy on a selection of networks on CIFAR and ImageNet. I was able to understand the core contribution and Figure 2 is very nicely designed. I think it would make it clearer, if the text can explain Eq. 9 better.