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While deep neural networks are a highly successful model class, their large memory footprint puts considerable strain on energy consumption, communication bandwidth, and storage requirements.
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Song Han, Huizi Mao, and William J Dally · 2016
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Beta-VAE: Learning basic visual concepts with a constrained variational framework
I. Higgins, L. Matthey, A. Pal, C. Burgess, X. Glorot, M. Botvinick, S. Mohamed, and A. Lerchner · 2017
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C. Louizos, K. Ullrich, and M. Welling · 2017
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The sample size required in importance sampling
S. Chatterjee and P. Diaconis · 2018
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Weightless: Lossy weight encoding for deep neural network compression
B. Reagen, U. Gupta, R. Adolf, M. M. Mitzenmacher, A. M. Rush, G.-Y. Wei, and D. Brooks · 2018
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