Fetching the paper…
Reading the bibliography…
While deep neural networks have been shown in recent years to outperform other machine learning methods in a wide range of applications, one of the biggest challenges with enabling deep neural networks for widespread deployment on edge devices such as mobile and other consumer devices is high computational and memory requirements.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
Binaryconnect: Training deep neural networks with binary weights during propagations
M. Courbariaux, Y. Bengio, and J.-P. David · 2015
Earlier work this paper cites.
Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
Earlier work this paper cites.
Xnor-net: Imagenet classification using binary convolutional neural networks
M. Rastegari, V. Ordonez, J. Redmon, and A. Farhadi · 2015
Earlier work this paper cites.
Squeezenet: Alexnet-level accuracy with 50x fewer parameters and < < 0.5mb model size
Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, and Kurt Keutzer · 2016
Earlier work this paper cites.
Fengfu Li, Bo Zhang, and Bin Liu · 2016
Cited alongside, same era.
M. Shafiee, F. Li, and A. Wong · 2016
Cited alongside, same era.
Deep learning with darwin: Evolutionary synthesis of deep neural networks
M. Shafiee, A. Mishra, and A. Wong · 2016
Cited alongside, same era.
Evolutionary synthesis of deep neural networks via synaptic cluster-driven genetic encoding
M. Shafiee and A. Wong · 2016
Cited alongside, same era.
Mobilenets: Efficient convolutional neural networks for mobile vision applications
A. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam · 2017
Closest in time.
Two-bit networks for deep learning on resource-constrained embedded devices
W. Meng, Z. Gu, M. Zhang, and Z. Wu · 2017
Closest in time.
Fixed-point optimization of deep neural networks with adaptive step size retraining
S. Shin, Y. Boo, and W. Sung · 2017
Closest in time.
Training ternary neural networks with exact proximal operator
P. Yin, S. Zhang, J. Xin, and Y. Qi · 2017
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…