143 citations · 170 across the 3 of their papers we have counts for
3 papers
cs.CV2018★ 10 cited
Precision Highway for Ultra Low-Precision Quantization
Eunhyeok Park, Dongyoung Kim, Sungjoo Yoo +1
Neural network quantization has an inherent problem called accumulated quantization error, which is the key obstacle towards ultra-low precision, e.g., 2- or 3-bit precision. To re…
cs.CV2018★ 17 cited
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation
Xiaoliang Dai, Peizhao Zhang, Bichen Wu +10
This paper proposes an efficient neural network (NN) architecture design methodology called Chameleon that honors given resource constraints. Instead of developing new building blo…
cs.CV2016★ 143 cited
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
Song Han, Jeff Pool, Sharan Narang +9
Modern deep neural networks have a large number of parameters, making them very hard to train. We propose DSD, a dense-sparse-dense training flow, for regularizing deep neural netw…