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A large fraction of Internet traffic is now driven by requests from mobile devices with relatively small screens and often stringent bandwidth requirements.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Williams, Ronald J · 1992
Earlier work this paper cites.
Long short-term memory
Hochreiter, S. and Schmidhuber, J · 1997
Earlier work this paper cites.
Image compression with neural networks–a survey
Jiang, J · 1999
Earlier work this paper cites.
Information technology–JPEG 2000 image coding system
ISO/IEC 15444-1 · 2000
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A., Conrad, A., Sheikh, H. R., and Simoncelli, E. P · 2004
Earlier work this paper cites.
Reducing the dimensionality of data with neural networks
Hinton, G. E. and Salakhutdinov, R. R · 2006
Earlier work this paper cites.
On between-coefficient contrast masking of DCT basis functions
Ponomarenko, N., Silvestri, F., Egiazarian, K., Carli, M., Astola, J., and Lukin, V · 2007
Earlier work this paper cites.
Learning multiple layers of features from tiny images
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Using very deep autoencoders for content-based image retrieval
Krizhevsky, A. and Hinton, G. E · 2011
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Kingma, D. P. and Ba, J · 2014
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Recurrent neural network regularization
Zaremba, W., Sutskever, I., and Vinyals, O · 2014
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BinaryConnect: Training deep neural networks with binary weights during propagations
Courbariaux, M., Bengio, Y., and David, J.-P · 2015
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Deep generative image models using a laplacian pyramid of adversarial networks
Denton, E., Chintala, S., Szlam, A., and Fergus, R · 2015
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WebP Compression Study
Google · 2015
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Draw: A recurrent neural network for image generation
Gregor, K., Danihelka, I., Graves, A., Rezende, D. J., and Wierstra, D · 2015
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Long, J., Shelhamer, E., and Darrell, T · 2014
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Sequence to sequence learning with neural networks
Sutskever, I., Vinyals, O., and Le, Q. V · 2014
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Techniques for learning binary stochastic feedforward neural networks
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Convolutional LSTM network: A machine learning approach for precipitation nowcasting
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