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With the development of deep neural networks, the size of network models becomes larger and larger.
Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Binaryconnect: Training deep neural networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, and Jean-Pierre David · 2015
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Learning both weights and connections for efficient neural network
Song Han, Jeff Pool, John Tran, and William Dally · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Compression of deep convolutional neural networks for fast and low power mobile applications
Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, and Dongjun Shin · 2015
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Tensorizing neural networks
Alexander Novikov, Dmitrii Podoprikhin, Anton Osokin, and Dmitry P Vetrov · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Binarized neural networks
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio · 2016
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Fengfu Li, Bo Zhang, and Bin Liu · 2016
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Xnor-net: Imagenet classification using binary convolutional neural networks
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, and Ali Farhadi · 2016
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Learning structured sparsity in deep neural networks
Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li · 2016
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Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
Shuchang Zhou, Yuxin Wu, Zekun Ni, Xinyu Zhou, He Wen, and Yuheng Zou · 2016
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Deep learning with low precision by half-wave gaussian quantization
Zhaowei Cai, Xiaodong He, Jian Sun, and Nuno Vasconcelos · 2017
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Network sketching: Exploiting binary structure in deep cnns
Yiwen Guo, Anbang Yao, Hao Zhao, and Yurong Chen · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Pruning filters for efficient convnets
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf · 2017
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Zhezhi He and Deliang Fan · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Quantization and training of neural networks for efficient integer-arithmetic-only inference
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, and Dmitry Kalenichenko · 2018
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Extremely low bit neural network: Squeeze the last bit out with admm
Cong Leng, Zesheng Dou, Hao Li, Shenghuo Zhu, and Rong Jin · 2018
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Synaptic strength for convolutional neural network
Chen Lin, Zhao Zhong, Wei Wu, and Junjie Yan · 2018
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Towards accurate binary convolutional neural network
Xiaofan Lin, Cong Zhao, and Wei Pan · 2017
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Thinet: A filter level pruning method for deep neural network compression
Jian-Hao Luo, Jianxin Wu, and Weiyao Lin · 2017
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Pytorch: Tensors and dynamic neural networks in python with strong gpu acceleration
Adam Paszke, Sam Gross, Soumith Chintala, and Gregory Chanan · 2017
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Trained ternary quantization
Chenzhuo Zhu, Song Han, Huizi Mao, and William J Dally · 2017
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Heterogeneous bitwidth binarization in convolutional neural networks
Joshua Fromm, Shwetak Patel, and Matthai Philipose · 2018
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Pruning filter via geometric median for deep convolutional neural networks acceleration
Yang He, Ping Liu, Ziwei Wang, and Yi Yang · 2018
Cited alongside, same era.
Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun
Cited in the paper.
Bo Peng, Wenming Tan, Zheyang Li, Shun Zhang, Di Xie, and Shiliang Pu · 2018
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Learning discrete weights using the local reparameterization trick
Oran Shayer, Dan Levi, and Ethan Fetaya · 2018
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Tbn: Convolutional neural network with ternary inputs and binary weights
Diwen Wan, Fumin Shen, Li Liu, Fan Zhu, Jie Qin, Ling Shao, and Heng Tao Shen · 2018
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Towards effective low-bitwidth convolutional neural networks
Bohan Zhuang, Chunhua Shen, Mingkui Tan, Lingqiao Liu, and Ian Reid · 2018
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Regularizing activation distribution for training binarized deep networks
Ruizhou Ding, Ting-Wu Chin, Zeye Liu, and Diana Marculescu · 2019
Closest in time.
Learning to quantize deep networks by optimizing quantization intervals with task loss
Sangil Jung, Changyong Son, Seohyung Lee, Jinwoo Son, Jae-Joon Han, Youngjun Kwak, Sung Ju Hwang, and Changkyu Choi · 2019
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