Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing
Author:
Affiliation:
1. School of Electrical and Computer Engineering, UNIST, Ulsan, Korea, Neural Processing Research Center, Seoul National Universtiy, Seoul, Korea
Funder
National Research Foundation of Korea
Institute for Information and communications Technology Planning & Evaluation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3316781.3317916
Reference12 articles.
1. Return of the Devil in the Details: Delving Deep into Convolutional Nets
2. F. N. Iandola etal 2016. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size. arXiv:1602.07360 (2016). F. N. Iandola et al. 2016. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size. arXiv:1602.07360 (2016).
3. Caffe
4. A. Krizhevsky I. Sutskever and G. E. Hinton. 2012. ImageNet Classification with Deep Convolutional Neural Networks. In Advances in Neural Information Processing Systems 25. Curran Associates Inc. 1097--1105. A. Krizhevsky I. Sutskever and G. E. Hinton. 2012. ImageNet Classification with Deep Convolutional Neural Networks. In Advances in Neural Information Processing Systems 25. Curran Associates Inc. 1097--1105.
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