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MXNet is a multi-language machine learning (ML) library to ease the development of ML algorithms, especially for deep neural networks.
Torch7: A matlab-like environment for machine learning
Ronan Collobert, Koray Kavukcuoglu, and Clément Farabet · 2011
Earlier work this paper cites.
Theano: new features and speed improvements
Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian Goodfellow, Arnaud Bergeron, Nicolas Bouchard, David Warde-Farley, and Yoshua Bengio · 2012
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Large scale distributed deep networks
J. Dean, G. Corrado, R. Monga, K. Chen, M. Devin, Q. Le, M. Mao, M. Ranzato, A. Senior, P. Tucker, K. Yang, and A. Ng · 2012
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Caffe: Convolutional architecture for fast feature embedding
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell · 2014
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Scaling distributed machine learning with the parameter server
M. Li, D. G. Andersen, J. Park, A. J. Smola, A. Amhed, V. Josifovski, J. Long, E. Shekita, and B. Y. Su · 2014
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Communication efficient distributed machine learning with the parameter server
M. Li, D. G. Andersen, A. J. Smola, and K. Yu · 2014
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Purine: A bi-graph based deep learning framework
Min Lin, Shuo Li, Xuan Luo, and Shuicheng Yan · 2014
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2014
Cited alongside, same era.
Minerva: A scalable and highly efficient training platform for deep learning, 2014
Minjie Wang, Tianjun Xiao, Jianpeng Li, Jiaxing Zhang, Chuntao Hong, and Zheng Zhang · 2014
Cited alongside, same era.
Easy benchmarking of all public open-source implementations of convnets, 2015
Soumith Chintala · 2015
Cited alongside, same era.
Chainer: A powerful, flexible, and intuitive framework of neural networks, 2015
Chainer Developers · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Tensorflow: Large-scale machine learning on heterogeneous systems
Abadi Martın, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Closest in time.
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