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cs.NE2016★ 1.8k cited
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
Shuchang Zhou, Yuxin Wu, Zekun Ni +3
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…
cs.NE2015★ 4 cited
Compression of Fully-Connected Layer in Neural Network by Kronecker Product
Shuchang Zhou, Jia-Nan Wu
In this paper we propose and study a technique to reduce the number of parameters and computation time in fully-connected layers of neural networks using Kronecker product, at a mi…