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Recently low displacement rank (LDR) matrices, or so-called structured matrices, have been proposed to compress large-scale neural networks.
Approximation by superpositions of a sigmoidal function
George Cybenko · 1989
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Multilayer feedforward networks are universal approximators
Kurt Hornik, Maxwell Stinchcombe, and Halbert White · 1989
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Approximation capabilities of multilayer feedforward networks
Kurt Hornik · 1991
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Universal approximation bounds for superpositions of a sigmoidal function
Andrew R Barron · 1993
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Polynomial and matrix computations volume 1: Fundamental algorithms
Dario Bini, Victor Pan, and Wayne Eberly · 1996
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Structured matrices and polynomials: unified superfast algorithms
Victor Pan · 2001
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Shallow vs. deep sum-product networks
Olivier Delalleau and Yoshua Bengio · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Exploiting linear structure within convolutional networks for efficient evaluation
Emily L Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, and Rob Fergus · 2014
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Compressing deep convolutional networks using vector quantization
Yunchao Gong, Liu Liu, Ming Yang, and Lubomir Bourdev · 2014
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Speeding up convolutional neural networks with low rank expansions
Max Jaderberg, Andrea Vedaldi, and Andrew Zisserman · 2014
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Song Han, Huizi Mao, and William J Dally · 2015
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Sparse convolutional neural networks
Baoyuan Liu, Min Wang, Hassan Foroosh, Marshall Tappen, and Marianna Pensky · 2015
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Estimating the norms of random circulant and toeplitz matrices and their inverses
Victor Y Pan, John Svadlenka, and Liang Zhao · 2015
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Structured transforms for small-footprint deep learning
Vikas Sindhwani, Tara Sainath, and Sanjiv Kumar · 2015
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Shiyu Liang and R Srikant · 2016
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On the number of linear regions of deep neural networks
Guido F Montufar, Razvan Pascanu, Kyunghyun Cho, and Yoshua Bengio · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
Cited alongside, same era.
An exploration of parameter redundancy in deep networks with circulant projections
Yu Cheng, Felix X Yu, Rogerio S Feris, Sanjiv Kumar, Alok Choudhary, and Shi-Fu Chang · 2015
Cited alongside, same era.
Matus Telgarsky · 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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