@inproceedings {hubara2016binarized,
	title = {Binarized neural networks},
	year = {2016},
	pages = {4107{\textendash}4115},
	keywords = {Deep Learning, ref},
	author = {Hubara, Itay and Courbariaux, Matthieu and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua}
}
@article {courbariaux2016binarized,
	title = {Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1},
	journal = {arXiv preprint arXiv:1602.02830},
	year = {2016},
	keywords = {Deep Learning, ref},
	author = {Courbariaux, Matthieu and Hubara, Itay and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua}
}
@article {kim2016bitwise,
	title = {Bitwise neural networks},
	journal = {arXiv preprint arXiv:1601.06071},
	year = {2016},
	keywords = {Deep Learning, ref},
	author = {Kim, Minje and Smaragdis, Paris}
}
@inproceedings {rastegari2016xnor,
	title = {Xnor-net: Imagenet classification using binary convolutional neural networks},
	year = {2016},
	pages = {525{\textendash}542},
	publisher = {Springer},
	keywords = {Deep Learning, ref},
	author = {Rastegari, Mohammad and Ordonez, Vicente and Redmon, Joseph and Farhadi, Ali}
}
@inproceedings {courbariaux2015binaryconnect,
	title = {Binaryconnect: Training deep neural networks with binary weights during propagations},
	year = {2015},
	pages = {3123{\textendash}3131},
	keywords = {Deep Learning, ref},
	author = {Courbariaux, Matthieu and Bengio, Yoshua and David, Jean-Pierre}
}
@article {lecun2015deep,
	title = {Deep learning},
	journal = {Nature},
	volume = {521},
	number = {7553},
	year = {2015},
	pages = {436{\textendash}444},
	publisher = {Nature Research},
	keywords = {Deep Learning, ref},
	author = {LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey}
}
@article {schmidhuber2015deep,
	title = {Deep learning in neural networks: An overview},
	journal = {Neural networks},
	volume = {61},
	year = {2015},
	pages = {85{\textendash}117},
	publisher = {Elsevier},
	keywords = {Deep Learning, ref},
	author = {Schmidhuber, J{\"u}rgen}
}
@inproceedings {gupta2015deep,
	title = {Deep learning with limited numerical precision},
	year = {2015},
	pages = {1737{\textendash}1746},
	keywords = {Deep Learning, ref},
	author = {Gupta, Suyog and Agrawal, Ankur and Gopalakrishnan, Kailash and Narayanan, Pritish}
}
@inproceedings {szegedy2015going,
	title = {Going deeper with convolutions},
	year = {2015},
	pages = {1{\textendash}9},
	keywords = {Deep Learning, ref},
	author = {Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke, Vincent and Rabinovich, Andrew}
}
@article {dally2015high,
	title = {High-performance hardware for machine learning},
	journal = {NIPS Tutorial},
	year = {2015},
	keywords = {Deep Learning, ref},
	url = {https://www.microsoft.com/en-us/research/video/tutorial-high-performance-hardware-for-machine-learning/?from=http\%3A\%2F\%2Fresearch.microsoft.com\%2Fapps\%2Fvideo\%2F\%3Fid\%3D259571},
	author = {Dally, William}
}
@inproceedings {zhang2015optimizing,
	title = {Optimizing fpga-based accelerator design for deep convolutional neural networks},
	year = {2015},
	pages = {161{\textendash}170},
	publisher = {ACM},
	keywords = {Deep Learning, ref},
	author = {Zhang, Chen and Li, Peng and Sun, Guangyu and Guan, Yijin and Xiao, Bingjun and Cong, Jason}
}
@article {putnam2015reconfigurable,
	title = {A reconfigurable fabric for accelerating large-scale datacenter services},
	journal = {IEEE Micro},
	volume = {35},
	number = {3},
	year = {2015},
	pages = {10{\textendash}22},
	publisher = {IEEE},
	keywords = {Deep Learning, ref},
	author = {Putnam, Andrew and Caulfield, Adrian M and Chung, Eric S and Chiou, Derek and Constantinides, Kypros and Demme, John and Esmaeilzadeh, Hadi and Fowers, Jeremy and Gopal, Gopi Prashanth and Gray, Jan and others}
}
@inproceedings {chen2014dadiannao,
	title = {Dadiannao: A machine-learning supercomputer},
	year = {2014},
	pages = {609{\textendash}622},
	publisher = {IEEE Computer Society},
	keywords = {Deep Learning, ref},
	author = {Chen, Yunji and Luo, Tao and Liu, Shaoli and Zhang, Shijin and He, Liqiang and Wang, Jia and Li, Ling and Chen, Tianshi and Xu, Zhiwei and Sun, Ninghui and others}
}
@inproceedings {chen2014diannao,
	title = {Diannao: A small-footprint high-throughput accelerator for ubiquitous machine-learning},
	volume = {49},
	number = {4},
	year = {2014},
	pages = {269{\textendash}284},
	publisher = {ACM},
	keywords = {Deep Learning, ref},
	author = {Chen, Tianshi and Du, Zidong and Sun, Ninghui and Wang, Jia and Wu, Chengyong and Chen, Yunji and Temam, Olivier}
}
@inproceedings {ouyang2014sda,
	title = {SDA: Software-defined accelerator for large-scale DNN systems},
	year = {2014},
	pages = {1{\textendash}23},
	publisher = {IEEE},
	keywords = {Deep Learning, ref},
	author = {Ouyang, Jian and Lin, Shiding and Qi, Wei and Wang, Yong and Yu, Bo and Jiang, Song}
}
@book {james2013introduction,
	title = {An introduction to statistical learning},
	volume = {112},
	year = {2013},
	publisher = {Springer},
	organization = {Springer},
	keywords = {Deep Learning, ref},
	url = {https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about},
	author = {James, Gareth and Witten, Daniela and Hastie, Trevor and Tibshirani, Robert}
}
@inproceedings {krizhevsky2012imagenet,
	title = {Imagenet classification with deep convolutional neural networks},
	year = {2012},
	pages = {1097{\textendash}1105},
	keywords = {Deep Learning, ref},
	author = {Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E}
}
@inbook {bengio2012practical,
	title = {Practical recommendations for gradient-based training of deep architectures},
	booktitle = {Neural networks: Tricks of the trade},
	year = {2012},
	pages = {437{\textendash}478},
	publisher = {Springer},
	organization = {Springer},
	keywords = {Deep Learning, ref},
	author = {Bengio, Yoshua}
}
@inproceedings {zinkevich2010parallelized,
	title = {Parallelized stochastic gradient descent},
	year = {2010},
	pages = {2595{\textendash}2603},
	keywords = {Deep Learning, ref},
	author = {Zinkevich, Martin and Weimer, Markus and Li, Lihong and Smola, Alex J}
}
@inproceedings {perez2009supervised,
	title = {A supervised learning method for neural networks based on sensitivity analysis with automatic regularization},
	year = {2009},
	pages = {157{\textendash}164},
	publisher = {Springer},
	keywords = {Deep Learning, ref},
	author = {P{\'e}rez-S{\'a}nchez, Beatriz and Fontenla-Romero, Oscar and Guijarro-Berdi{\~n}as, Bertha}
}
@book {friedman2001elements,
	title = {The elements of statistical learning},
	volume = {1},
	year = {2001},
	publisher = {Springer series in statistics New York},
	organization = {Springer series in statistics New York},
	keywords = {Deep Learning, ref},
	url = {https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about},
	author = {Friedman, Jerome and Hastie, Trevor and Tibshirani, Robert}
}
