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Despite their prevalence, deep networks are poorly understood.
Optimal brain damage
Yann LeCun, John S. Denker, and Sara A. Solla · 1990
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Model compression
Cristian Bucila, Rich Caruana, and Alexandru Niculescu-Mizil · 2006
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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MNIST handwritten digit database
Yann LeCun and Corinna Cortes · 2010
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Novel dataset for fine-grained image categorization
Aditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao, and Li Fei-Fei · 2011
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Visualizing and understanding convolutional networks
Matthew D. Zeiler and Rob Fergus · 2013
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Fitnets: Hints for thin deep nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Cited alongside, same era.
Global optimality in tensor factorization, deep learning, and beyond
Benjamin D. Haeffele and René Vidal · 2015
Cited alongside, same era.
Song Han, Huizi Mao, and William J. Dally · 2015
Cited alongside, same era.
Cifar-10 (canadian institute for advanced research)
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton
Cited in the paper.
Inceptionism: Going deeper into neural networks
Alexander Mordvintsev, Christopher Olah, and Mike Tyka
Cited in the paper.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Later among the works it cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
Later among the works it cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Later among the works it cites.
Understanding neural networks through deep visualization
Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson · 2015
Later among the works it cites.
A genetic programming approach to designing convolutional neural network architectures
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Masanori Suganuma, Shinichi Shirakawa, and Tomoharu Nagao · 2017
Later among the works it cites.