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20172023
most citedAutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks

8 citations · 16 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.LG2019

A Channel-Pruned and Weight-Binarized Convolutional Neural Network for Keyword Spotting

Jiancheng Lyu, Spencer Sheen

We study channel number reduction in combination with weight binarization (1-bit weight precision) to trim a convolutional neural network for a keyword spotting (classification) ta…

cs.LG2019

Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Penghang Yin, Jiancheng Lyu, Shuai Zhang +3

Training activation quantized neural networks involves minimizing a piecewise constant function whose gradient vanishes almost everywhere, which is undesirable for the standard bac…

cs.LG20198 cited

AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks

Jiancheng Lyu, Shuai Zhang, Yingyong Qi +1

ShuffleNet is a state-of-the-art light weight convolutional neural network architecture. Its basic operations include group, channel-wise convolution and channel shuffling. However…

cs.LG2018

Median Binary-Connect Method and a Binary Convolutional Neural Nework for Word Recognition

Spencer Sheen, Jiancheng Lyu

We propose and study a new projection formula for training binary weight convolutional neural networks. The projection formula measures the error in approximating a full precision…

cs.LG2018

Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks

Penghang Yin, Shuai Zhang, Jiancheng Lyu +3

Quantized deep neural networks (QDNNs) are attractive due to their much lower memory storage and faster inference speed than their regular full precision counterparts. To maintain…