27 citations · 28 across the 5 of their papers we have counts for
5 papers
BAMSProd: A Step towards Generalizing the Adaptive Optimization Methods to Deep Binary Model
Junjie Liu, Dongchao Wen, Deyu Wang +4
Recent methods have significantly reduced the performance degradation of Binary Neural Networks (BNNs), but guaranteeing the effective and efficient training of BNNs is an unsolved…
QuantNet: Learning to Quantize by Learning within Fully Differentiable Framework
Junjie Liu, Dongchao Wen, Deyu Wang +4
Despite the achievements of recent binarization methods on reducing the performance degradation of Binary Neural Networks (BNNs), gradient mismatching caused by the Straight-Throug…
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers
Junjie Liu, Zhe Xu, Runbin Shi +2
We present a novel network pruning algorithm called Dynamic Sparse Training that can jointly find the optimal network parameters and sparse network structure in a unified optimizat…
DupNet: Towards Very Tiny Quantized CNN with Improved Accuracy for Face Detection
Hongxing Gao, Wei Tao, Dongchao Wen +4
Deploying deep learning based face detectors on edge devices is a challenging task due to the limited computation resources. Even though binarizing the weights of a very tiny netwo…
Knowledge Representing: Efficient, Sparse Representation of Prior Knowledge for Knowledge Distillation
Junjie Liu, Dongchao Wen, Hongxing Gao +4
Despite the recent works on knowledge distillation (KD) have achieved a further improvement through elaborately modeling the decision boundary as the posterior knowledge, their per…