Training deep neural networks with low precision multiplications
暂无分享,去创建一个
Yoshua Bengio | Jean-Pierre David | Matthieu Courbariaux | Yoshua Bengio | Matthieu Courbariaux | J. David
[1] J. L. Holt,et al. Back propagation simulations using limited precision calculations , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[2] Patrice Y. Simard,et al. Backpropagation without Multiplication , 1993, NIPS.
[3] R. L. Haggard,et al. A fixed point implementation of the backpropagation learning algorithm , 1994, Proceedings of SOUTHEASTCON '94.
[4] Brian Kingsbury,et al. Spert-II: A Vector Microprocessor System , 1996, Computer.
[5] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[6] Adi Shraibman,et al. Rank, Trace-Norm and Max-Norm , 2005, COLT.
[7] Kassem Kalach,et al. Hardware Complexity of Modular Multiplication and Exponentiation , 2007, IEEE Transactions on Computers.
[8] Shawki Areibi,et al. The Impact of Arithmetic Representation on Implementing MLP-BP on FPGAs: A Study , 2007, IEEE Transactions on Neural Networks.
[9] Jusung Park,et al. Design and implementation of 16-bit fixed point digital signal processor , 2008, 2008 International SoC Design Conference.
[10] Kunle Olukotun,et al. A highly scalable Restricted Boltzmann Machine FPGA implementation , 2009, 2009 International Conference on Field Programmable Logic and Applications.
[11] Quoc V. Le,et al. Scalable learning for object detection with GPU hardware , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[12] Yann LeCun,et al. What is the best multi-stage architecture for object recognition? , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[13] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[14] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[15] Andrew Y. Ng,et al. Reading Digits in Natural Images with Unsupervised Feature Learning , 2011 .
[16] Berin Martini,et al. NeuFlow: A runtime reconfigurable dataflow processor for vision , 2011, CVPR 2011 WORKSHOPS.
[17] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[18] Vincent Vanhoucke,et al. Improving the speed of neural networks on CPUs , 2011 .
[19] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[20] Marc'Aurelio Ranzato,et al. Large Scale Distributed Deep Networks , 2012, NIPS.
[21] Razvan Pascanu,et al. Theano: new features and speed improvements , 2012, ArXiv.
[22] E. Culurciello,et al. NeuFlow: Dataflow vision processing system-on-a-chip , 2012, 2012 IEEE 55th International Midwest Symposium on Circuits and Systems (MWSCAS).
[23] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[24] Rob Fergus,et al. Stochastic Pooling for Regularization of Deep Convolutional Neural Networks , 2013, ICLR.
[25] Ian J. Goodfellow,et al. Pylearn2: a machine learning research library , 2013, ArXiv.
[26] Yoshua Bengio,et al. Maxout Networks , 2013, ICML.
[27] Ninghui Sun,et al. DianNao: a small-footprint high-throughput accelerator for ubiquitous machine-learning , 2014, ASPLOS.
[28] Jia Wang,et al. DaDianNao: A Machine-Learning Supercomputer , 2014, 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture.
[29] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[30] Pritish Narayanan,et al. Deep Learning with Limited Numerical Precision , 2015, ICML.