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Many natural language processing applications use language models to generate text.
Learning internal representations by back-propagating errors
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Daume III, H., Langford, J., and Marcu, D · 2009
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Imagenet: a large-scale hierarchical image database
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Direct loss minimization for structured prediction
McAllester, D., Hazan, T., and Keshet, J · 2010
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Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollar, P., and Zitnick, C.L · 2014
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Recurrent models of visual attention
Mnih, V., Heess N., Graves, A., and Kavukcuoglu, K · 2014
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Sutskever, Ilya, Vinyals, Oriol, and Le, Quoc · 2014
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Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., and Bengio, Y · 2015
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Scheduled sampling for sequence prediction with recurrent neural networks
Bengio, S., Vinyals, O., Jaitly, N., and Shazeer, N · 2015
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A reduction of imitation learning and structured prediction to no-regret online learning
Ross, S., Gordon, G.J., and Bagnell, J.A · 2011
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Rosti, Antti-Veikko I, Zhang, Bing, Matsoukas, Spyros, and Schwartz, Richard · 2011
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Maximum expected bleu training of phrase and lexicon translation models
He, X. and Deng, L · 2012
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Decoder integration and expected bleu training for recurrent neural network language models
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Multiple object recognition with visual attention
Ba, J.L., Mnih, V., and Kavukcuoglu, K
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A neural attention model for abstractive sentence summarization
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