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Weight pruning and weight quantization are two important categories of DNN model compression.
Distributed optimization and statistical learning via the alternating direction method of multipliers
Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J., et al.: · 2011
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
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Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2014
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Exploiting linear structure within convolutional networks for efficient evaluation
Denton, E.L., Zaremba, W., Bruna, J., LeCun, Y., Fergus, R.: · 2014
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Learning both weights and connections for efficient neural network
Han, S., Pool, J., Tran, J., Dally, W.: · 2015
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Binaryconnect: Training deep neural networks with binary weights during propagations
Courbariaux, M., Bengio, Y., David, J.P.: · 2015
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Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2015
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Designing energy-efficient convolutional neural networks using energy-aware pruning
Yang, T.J., Chen, Y.H., Sze, V.: · 2016
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Dynamic network surgery for efficient dnns
Guo, Y., Yao, A., Chen, Y.: · 2016
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Fixed point quantization of deep convolutional networks
Lin, D., Talathi, S., Annapureddy, S.: · 2016
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Quantized convolutional neural networks for mobile devices
Wu, J., Leng, C., Wang, Y., Hu, Q., Cheng, J.: · 2016
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Xnor-net: Imagenet classification using binary convolutional neural networks
Rastegari, M., Ordonez, V., Redmon, J., Farhadi, A.: · 2016
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Binarized neural networks
Hubara, I., Courbariaux, M., Soudry, D., El-Yaniv, R., Bengio, Y.: · 2016
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Convergence analysis of alternating direction method of multipliers for a family of nonconvex problems
Hong, M., Luo, Z.Q., Razaviyayn, M.: · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., Sun, J.: · 2016
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Nest: A neural network synthesis tool based on a grow-and-prune paradigm
Dai, X., Yin, H., Jha, N.K.: · 2017
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Learning to prune deep neural networks via layer-wise optimal brain surgeon
Designing energy-efficient convolutional neural networks using energy-aware pruning
Yang, T.J., Chen, Y.H., Sze, V.: · 2017
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On the linear convergence of the alternating direction method of multipliers
Hong, M., Luo, Z.Q.: · 2017
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Exploring the regularity of sparse structure in convolutional neural networks
Mao, H., Han, S., Pool, J., Li, W., Liu, X., Wang, Y., Dally, W.J.: · 2017
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On compressing deep models by low rank and sparse decomposition
Yu, X., Liu, T., Wang, X., Tao, D.: · 2017
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A systematic dnn weight pruning framework using alternating direction method of multipliers
Zhang, T., Ye, S., Zhang, K., Tang, J., Wen, W., Fardad, M., Wang, Y.: · 2018
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Dong, X., Chen, S., Pan, S.: · 2017
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Channel pruning for accelerating very deep neural networks
He, Y., Zhang, X., Sun, J.: · 2017
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Extremely low bit neural network: Squeeze the last bit out with admm
Leng, C., Li, H., Zhu, S., Jin, R.: · 2017
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Weighted-entropy-based quantization for deep neural networks
Park, E., Ahn, J., Yoo, S.: · 2017
Cited alongside, same era.
Incremental network quantization: Towards lossless cnns with low-precision weights
Zhou, A., Yao, A., Guo, Y., Xu, L., Chen, Y.: · 2017
Cited alongside, same era.
Nest: a neural network synthesis tool based on a grow-and-prune paradigm
Dai, X., Yin, H., Jha, N.K.: · 2017
Cited alongside, same era.
Zhang, T., Zhang, K., Ye, S., Li, J., Tang, J., Wen, W., Lin, X., Fardad, M., Wang, Y.: · 2018
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Zeroth-order online alternating direction method of multipliers: Convergence analysis and applications
Liu, S., Chen, J., Chen, P.Y., Hero, A.: · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.: · 2018
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Demystifying neural network filter pruning
Qin, Z., Yu, F., Liu, C., Chen, X.: · 2018
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Differentiable fine-grained quantization for deep neural network compression
Cheng, H.P., Huang, Y., Guo, X., Huang, Y., Yan, F., Li, H., Chen, Y.: · 2018
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Learning structured sparsity in deep neural networks
Wen, W., Wu, C., Wang, Y., Chen, Y., Li, H.: · 2082
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