Sep 20, 2017 � In this paper, we propose a novel progressive parameter pruning method for Convolutional Neural Network acceleration, named Structured�...
In this paper, we propose a novel progressive parameter pruning method for Con- volutional Neural Network acceleration, named Structured Probabilistic Pruning (�...
A novel progressive parameter pruning method, named Structured Probabilistic Pruning (SPP), which effectively prunes weights of convolutional layers in a�...
In this paper, we propose a novel progressive parameter pruning method for Convolutional Neural Network acceleration, named Structured Probabilistic Pruning (�...
Experiments show that, with 4x speedup, SPP can accelerate AlexNet with only 0.3% loss of top-5 accuracy and VGG-16 with 0.8% loss of top-5 accuracy in ImageNet�...
... Structured Probabilistic Pruning for Convolutional Neural Network Acceleration". Topics. pruning model-compression model-acceleration. Resources. Readme�...
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Neural network pruning techniques reduce the number of parameters without compromising predicting ability of a network. Many algo-.
Structured pruning is a popular way of convolutional neural network (CNN) acceleration. However, current state of the art pruning techniques require�...
Missing: Probabilistic | Show results with:Probabilistic
This work presents a probabilistic channel pruning method to accelerate Con- volutional Neural Networks (CNNs). Previous pruning methods often zero out.
A novel criterion to efficiently prune convolutional neural networks inspired by explaining nonlinear classification decisions in terms of input variables�...