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We introduce a method to train Quantized Neural Networks (QNNs) --- neural networks with extremely low precision (e.g., 1-bit) weights and activations, at run-time.
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Yoshua Bengio · 2013
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Adam Coates, Brody Huval, Tao Wang, David Wu, Bryan Catanzaro, and Ng Andrew · 2013
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Training deep neural networks with low precision multiplications
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Fast and robust neural network joint models for statistical machine translation
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Backpropagation for energy-efficient neuromorphic computing
Steve K Esser, Rathinakumar Appuswamy, Paul Merolla, John V Arthur, and Dharmendra S Modha · 2015
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Deep learning with limited numerical precision
Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, and Pritish Narayanan · 2015
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Huizi Mao Han, Song and William J. Dally · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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Compressing deep convolutional networks using vector quantization
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Spatially-sparse convolutional neural networks
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Fixed-point feedforward deep neural network design using weights+ 1, 0, and- 1
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Generalizing pooling functions in convolutional neural networks: Mixed, gated, and tree
Chen-Yu Lee, Patrick W Gallagher, and Zhuowen Tu · 2015
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglo, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidgeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharsan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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Inceptionism: Going deeper into neural networks, 2015
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Very deep convolutional networks for large-scale image recognition
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Efficient and accurate approximations of nonlinear convolutional networks
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Yodann: An ultra-low power convolutional neural network accelerator based on binary weights
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Deep neural networks are robust to weight binarization and other non-linear distortions
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Convolutional neural networks using logarithmic data representation
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Recurrent neural networks with limited numerical precision
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Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
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