most citedA Learning Framework for n-bit Quantized Neural Networks toward FPGAs

34 citations · 41 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2020★ 34 cited

A Learning Framework for n-bit Quantized Neural Networks toward FPGAs

Jun Chen, Liang Liu, Yong Liu +1

The quantized neural network (QNN) is an efficient approach for network compression and can be widely used in the implementation of FPGAs. This paper proposes a novel learning fram…

cs.LG2020★ 7 cited

Propagating Asymptotic-Estimated Gradients for Low Bitwidth Quantized Neural Networks

Jun Chen, Yong Liu, Hao Zhang +2

The quantized neural networks (QNNs) can be useful for neural network acceleration and compression, but during the training process they pose a challenge: how to propagate the grad…