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Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1

, , , , and . arXiv preprint arXiv:1602.02830, (2016)

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Semi-supervised Learning by Entropy Minimization., and . CAP, page 281-296. PUG, (2005)Training deep neural networks with low precision multiplications, , and . (2014)cite arxiv:1412.7024v5.pdfComment: 10 pages, 5 figures, Accepted as a workshop contribution at ICLR 2015.Use of genetic programming for the search of a new learning rule for neutral networks, , and . Proceedings of the 1994 IEEE World Congress on Computational Intelligence, 1, page 324--327. Orlando, Florida, USA, IEEE Press, (27-29 June 1994)IAPR keynote lecture IV: Deep learning.. ACPR, page xx. IEEE, (2015)Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model., and . IEEE Trans. Neural Networks, 19 (4): 713-722 (2008)A Neural Probabilistic Language Model, , , and . J. Mach. Learn. Res., (March 2003)Efficient Non-Parametric Function Induction in Semi-Supervised Learning., , and . AISTATS, Society for Artificial Intelligence and Statistics, (2005)Quick Training of Probabilistic Neural Nets by Importance Sampling., and . AISTATS, Society for Artificial Intelligence and Statistics, (2003)Learning a Synaptic Learning Rule, and . 751. Département d'Informatique et de Recherche Opérationelle, Université de Montréal, Montreal, Canada, (1990)Global Optimization of a Neural Network--Hidden Markov Model Hybrid, , , and . TR-SOCS-90.22. School of Computer Science, McGill University, Montreal, Canada, (1990)