Deep Learning with Low Precision by Half-Wave Gaussian Quantization
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Jian Sun | Nuno Vasconcelos | Zhaowei Cai | Xiaodong He | Xiaodong He | Jian Sun | Xiaodong He | N. Vasconcelos | Zhaowei Cai
[1] John B. Shoven,et al. I , Edinburgh Medical and Surgical Journal.
[2] P. J. Huber. Robust Estimation of a Location Parameter , 1964 .
[3] Frederick R. Forst,et al. On robust estimation of the location parameter , 1980 .
[4] S. P. Lloyd,et al. Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.
[5] Erkki Oja,et al. Independent component analysis: algorithms and applications , 2000, Neural Networks.
[6] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[7] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[8] Vincent Vanhoucke,et al. Improving the speed of neural networks on CPUs , 2011 .
[9] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[10] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[11] Geoffrey E. Hinton,et al. On rectified linear units for speech processing , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[12] Razvan Pascanu,et al. On the difficulty of training recurrent neural networks , 2012, ICML.
[13] Yoshua Bengio,et al. Maxout Networks , 2013, ICML.
[14] Misha Denil,et al. Predicting Parameters in Deep Learning , 2014 .
[15] Andrew Zisserman,et al. Speeding up Convolutional Neural Networks with Low Rank Expansions , 2014, BMVC.
[16] Qiang Chen,et al. Network In Network , 2013, ICLR.
[17] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[18] Joan Bruna,et al. Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation , 2014, NIPS.
[19] Ming Yang,et al. Compressing Deep Convolutional Networks using Vector Quantization , 2014, ArXiv.
[20] Song Han,et al. Learning both Weights and Connections for Efficient Neural Network , 2015, NIPS.
[21] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[23] Ross B. Girshick,et al. Fast R-CNN , 2015, 1504.08083.
[24] Yoshua Bengio,et al. BinaryConnect: Training Deep Neural Networks with binary weights during propagations , 2015, NIPS.
[25] Yoshua Bengio,et al. FitNets: Hints for Thin Deep Nets , 2014, ICLR.
[26] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[27] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[29] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[30] Yixin Chen,et al. Compressing Neural Networks with the Hashing Trick , 2015, ICML.
[31] Bin Liu,et al. Ternary Weight Networks , 2016, ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[32] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Sachin S. Talathi,et al. Fixed Point Quantization of Deep Convolutional Networks , 2015, ICML.
[34] Sachin S. Talathi,et al. Overcoming Challenges in Fixed Point Training of Deep Convolutional Networks , 2016, ArXiv.
[35] Song Han,et al. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding , 2015, ICLR.
[36] Yoshua Bengio,et al. Neural Networks with Few Multiplications , 2015, ICLR.
[37] Ran El-Yaniv,et al. Binarized Neural Networks , 2016, NIPS.
[38] Shuchang Zhou,et al. DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients , 2016, ArXiv.
[39] Forrest N. Iandola,et al. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size , 2016, ArXiv.
[40] Rogério Schmidt Feris,et al. A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection , 2016, ECCV.