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Deep quantization of neural networks (below eight bits) offers significant promise in reducing their compute and storage cost.
Learning internal representations by error propagation
D. E. Rumelhart, G. E. Hinton, and R. J. Williams · 1986
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Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. E. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. E. Hubbard, and L. D. Jackel · 1989
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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The Loss Surfaces of Multilayer Networks
A. Choromanska, M. Henaff, M. Mathieu, G. B. Arous, and Y. LeCun · 2015
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Binaryconnect: Training deep neural networks with binary weights during propagations
M. Courbariaux, Y. Bengio, and J. David · 2015
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Deep learning with limited numerical precision
S. Gupta, A. Agrawal, K. Gopalakrishnan, and P. Narayanan · 2015
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Sirius: An open end-to-end voice and vision personal assistant and its implications for future warehouse scale computers
J. Hauswald, M. Laurenzano, Y. Zhang, C. Li, A. Rovinski, A. Khurana, R. G. Dreslinski, T. N. Mudge, V. Petrucci, L. Tang, and J. Mars · 2015
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Deep learning
Y. LeCun, Y. Bengio, and G. E. Hinton · 2015
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Deep Learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
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Binarized Neural Networks
I. Hubara, M. Courbariaux, D. Soudry, R. El-Yaniv, and Y. Bengio · 2016
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Binarized neural networks
I. Hubara, M. Courbariaux, D. Soudry, R. El-Yaniv, and Y. Bengio · 2016
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Stripes: Bit-serial deep neural network computing
P. Judd, J. Albericio, T. H. Hetherington, T. M. Aamodt, and A. Moshovos · 2016
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F. Li and B. Liu · 2016
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XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
M. Rastegari, V. Ordonez, J. Redmon, and A. Farhadi · 2016
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DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
S. Zhou, Z. Ni, X. Zhou, H. Wen, Y. Wu, and Y. Zou · 2016
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Loss-aware binarization of deep networks
L. Hou, Q. Yao, and J. T. Kwok · 2017
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Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations
I. Hubara, M. Courbariaux, D. Soudry, R. El-Yaniv, and Y. Bengio · 2017
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Quantized neural networks: Training neural networks with low precision weights and activations
Learning low precision deep neural networks through regularization
Y. Choi, M. El-Khamy, and J. Lee · 2018
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Releq: A reinforcement learning approach for deep quantization of neural networks
A. T. Elthakeb, P. Pilligundla, A. Yazdanbakhsh, F. Mireshghallah, and H. Esmaeilzadeh · 2018
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Releq: A reinforcement learning approach for deep quantization of neural networks
A. T. Elthakeb, P. Pilligundla, A. Yazdanbakhsh, F. Mireshghallah, and H. Esmaeilzadeh · 2018
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Loss-aware weight quantization of deep networks
L. Hou and J. T. Kwok · 2018
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Joint training of low-precision neural network with quantization interval parameters
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I. Hubara, M. Courbariaux, D. Soudry, R. El-Yaniv, and Y. Bengio · 2017
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Efficient processing of deep neural networks: A tutorial and survey
V. Sze, Y. Chen, T. Yang, and J. S. Emer · 2017
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Incremental network quantization: Towards lossless cnns with low-precision weights
A. Zhou, A. Yao, Y. Guo, L. Xu, and Y. Chen · 2017
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Trained Ternary Quantization
C. Zhu, S. Han, H. Mao, and W. J. Dally · 2017
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Trained ternary quantization
C. Zhu, S. Han, H. Mao, and W. J. Dally · 2017
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Variational network quantization
J. Achterhold, J. M. Köhler, A. Schmeink, and T. Genewein · 2018
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Pact: Parameterized clipping activation for quantized neural networks
J. Choi, Z. Wang, S. Venkataramani, P. I.-J. Chuang, V. Srinivasan, and K. Gopalakrishnan · 2018
Cited alongside, same era.
S. Jung, C. Son, S. Lee, J. Son, Y. Kwak, J. Han, and C. Choi · 2018
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Visualizing the Loss Landscape of Neural Nets
H. Li, Z. Xu, G. Taylor, C. Studer, and T. Goldstein · 2018
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WRPN: Wide Reduced-Precision Networks
A. K. Mishra, E. Nurvitadhi, J. J. Cook, and D. Marr · 2018
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On periodic functions as regularizers for quantization of neural networks
M. Naumov, U. Diril, J. Park, B. Ray, J. Jablonski, and A. Tulloch · 2018
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Bit fusion: Bit-level dynamically composable architecture for accelerating deep neural network
H. Sharma, J. Park, N. Suda, L. Lai, B. Chau, V. Chandra, and H. Esmaeilzadeh · 2018
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Lq-nets: Learned quantization for highly accurate and compact deep neural networks
D. Zhang, J. Yang, D. Ye, and G. Hua · 2018
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Neural network distiller, June 2018
N. Zmora, G. Jacob, and G. Novik · 2018
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