2019
Same, Same But Different: Recovering Neural Network Quantization Error Through Weight Factorization
ICML 2019oral
Quantization of neural networks has become common practice, driven by the need for efficient implementations of deep neural networks on embedded devices. In this paper, we exploit an oft-overlooked degree of freedom in most networks - for a given layer, individual output channels can be scaled by an…