A Survey on Methods and Theories of Quantized Neural Networks

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A Survey on Methods and Theories of Quantized Neural Networks

13 August 2018

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Papers citing "A Survey on Methods and Theories of Quantized Neural Networks"

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Title
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,305 0 11 Feb 2015
Deep Learning with Limited Numerical Precision Suyog Gupta A. Agrawal K. Gopalakrishnan P. Narayanan HAI 207 2,048 0 09 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 326 18,625 0 06 Feb 2015
Compressing Deep Convolutional Networks using Vector Quantization Yunchao Gong Liu Liu Ming Yang Lubomir D. Bourdev MQ 165 1,170 0 18 Dec 2014
Convolutional Neural Networks at Constrained Time Cost Kaiming He Jian Sun 3DV 88 1,292 0 04 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 477 43,658 0 17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,386 0 04 Sep 2014
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation Yoshua Bengio Nicholas Léonard Aaron Courville 384 3,135 0 15 Aug 2013
Predicting Parameters in Deep Learning Misha Denil B. Shakibi Laurent Dinh MarcÁurelio Ranzato Nando de Freitas OOD 200 1,319 0 03 Jun 2013