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Parameter pruning is a promising approach for CNN compression and acceleration by eliminating redundant model parameters with tolerable performance loss.
High performance convolutional neural networks for document processing
K. Chellapilla, S. Puri, and P. Simard · 2006
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Model selection and estimation in regression with grouped variables
M. Yuan and Y. Lin · 2006
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ImageNet: A large-scale hierarchical iage database
J. Deng, W. Dong, R. Socher, L. J. Li, K. Li, and L. Feifei · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
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ImageNet classification with deep convolutional neural networks
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cuDNN: Efficient primitives for deep learning
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Caffe: Convolutional architecture for fast feature embedding
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Very deep convolutional networks for large-scale image recognition
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Compressing neural networks with the hashing trick
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Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
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Compact deep convolutional neural networks with coarse pruning
S. Anwar and W. Sung · 2016
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M. Courbariaux and Y. Bengio · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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SqueezeNet: Alexnet-level accuracy with 50x fewer parameters and < < 0.5MB model size
F. Iandola, M. Moskewicz, and K. Ashraf · 2016
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Speeding-up convolutional neural networks using fine-tuned CP-decomposition
V. Lebedev, Y. Ganin, M. Rakhuba, I. Oseledets, and V. Lempitsky · 2016
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Channel pruning for accelerating very deep neural networks
Y. He, X. Zhang, and J. Sun · 2017
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MobileNets: Efficient convolutional neural networks for mobile vision applications
A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam · 2017
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Pruning filters for efficient convnets
H. Li, A. Kadav, I. Durdanovic, H. Samet, and H. P. Graf · 2017
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Pruning convolutional neural networks for resource efficient inference
P. Molchanov, S. Tyree, and T. Karras · 2017
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Efficient processing of deep neural networks: A tutorial and survey
V. Sze, Y. H. Chen, T. J. Yang, and J. Emer · 2017
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How transferable are features in deep neural networks?
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson
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X. Zhang, X. Zhou, M. Lin, and J. Sun · 2017
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Auto-balanced filter pruning for efficient convolutional neural networks
X. Ding, G. Ding, J. Han, and S. Tang · 2018
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AMC: Automl for model compression and acceleration on mobile devices
Y. He, J. Lin, Z. Liu, H. Wang, L.-J. Li, and S. Han · 2018
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Structured probabilistic pruning for convolutional neural network acceleration
H. Wang, Q. Zhang, Y. Wang, and H. Hu · 2018
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Shift-based primitives for efficient convolutional neural networks
H. Zhong, X. Liu, Y. He, Y. Ma, and K. Kitani · 2018
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