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A low precision deep neural network training technique for producing sparse, ternary neural networks is presented.
Simonyan, Karen and Zisserman, Andrew. Very deep convolutional networks for large-scale image recognition (2014)
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Luong, Minh-Thang, Pham, Hieu, and Manning, Christo- pher D. Effective approaches to attention-based neural machine translation (2015)
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Courbariaux, Matthieu, Bengio, Yoshua, and David, Jean-Pierre. Binaryconnect: Training deep neural networks with binary weights during propagations (2015)
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Han, Song, Mao, Huizi, and Dally, William J. Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding. In International Conference on Learning Representations (2015)
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Han, Song, Pool, Jeff, Tran, John, and Dally, William. Learning both weights and connections for efficient neural network. In Advances in Neural Information Processing Systems (NIPS), pp. 1135–1143 (2015)
2015
Cited alongside, same era.
Courbariaux, Matthieu and Bengio, Yoshua. Binarynet: Training deep neural networks with weights and activations constrained to +1 or -1 (2016)
2016
Cited alongside, same era.
Li, Fengfu and Liu, Bin. Ternary weight networks (2016)
2016
Cited alongside, same era.
Venkatesh, Ganesh, Nurvitadhi, Eriko, and Marr, Debbie. Accelerating deep convolutional networks using low-precision and sparsity (2016)
2016
Cited alongside, same era.
Ardakani, Arash, Condo, Carlo, and Gross, Warren J. Sparsely-connected neural networks: Towards efficient VLSI implementation of deep neural networks (2016)
2016
Later among the works it cites.
Umuroglu, Yaman, Fraser, Nicholas J., Gambardella, Giulio, Blott, Michaela, Leong, Philip Heng Wai, Jahre, Magnus, and Vissers, Kees A. FINN: A framework for fast, scalable binarized neural network inference (2016)
2016
Later among the works it cites.
Fraser, Nicholas J., Umuroglu, Yaman, Gambardella, Giulio, Blott, Michaela, Leong, Philip Heng Wai, Jahre, Magnus, and Vissers, Kees A. Scaling binarized neural networks on reconfigurable logic (2017)
2017
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