32 citations · 32 across the 2 of their papers we have counts for
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cs.CV2021
An Information Theory-inspired Strategy for Automatic Network Pruning
Xiawu Zheng, Yuexiao Ma, Teng Xi +6
Despite superior performance on many computer vision tasks, deep convolution neural networks are well known to be compressed on devices that have resource constraints. Most existin…
cs.CV2021
Carrying out CNN Channel Pruning in a White Box
Yuxin Zhang, Mingbao Lin, Chia-Wen Lin +5
Channel Pruning has been long studied to compress CNNs, which significantly reduces the overall computation. Prior works implement channel pruning in an unexplainable manner, which…
cs.LG2021
ReCU: Reviving the Dead Weights in Binary Neural Networks
Zihan Xu, Mingbao Lin, Jianzhuang Liu +5
Binary neural networks (BNNs) have received increasing attention due to their superior reductions of computation and memory. Most existing works focus on either lessening the quant…