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Recurrent neural networks (RNNs) were recently proposed for the session-based recommendation task.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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Recommender systems in e-commerce
J. B. Schafer, J. Konstan, and J. Riedl · 1999
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Item-based collaborative filtering recommendation algorithms
B. M. Sarwar, G. Karypis, J. A. Konstan, and J. Riedl · 2001
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Restricted boltzmann machines for collaborative filtering
R. Salakhutdinov, A. Mnih, and G. Hinton · 2007
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Maximum margin matrix factorization for collaborative ranking
M. Weimer, A. Karatzoglou, Q. V. Le, and A. J. Smola · 2007
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Factorization meets the neighborhood: a multifaceted collaborative filtering model
Y. Koren · 2008
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Matrix factorization techniques for recommender systems
Y. Koren, R. M. Bell, and C. Volinsky · 2009
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A scalable hierarchical distributed language model
A. Mnih and G. E. Hinton · 2009
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Pairwise preference regression for cold-start recommendation
S.-T. Park and W. Chu · 2009
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A new learning paradigm: Learning using privileged information
V. Vapnik and A. Vashist · 2009
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Parsing Natural Scenes and Natural Language with Recursive Neural Networks
R. Socher, C. C. Lin, A. Y. Ng, and C. D. Manning · 2011
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Speech recognition with deep recurrent neural networks
A. Graves, A. Mohamed, and G. E. Hinton · 2013
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Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean · 2013
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Return of the devil in the details: Delving deep into convolutional nets
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
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Empirical evaluation of gated recurrent neural networks on sequence modeling
J. Chung, Ç. Gülçehre, K. Cho, and Y. Bengio · 2014
Cited alongside, same era.
Dropout: A simple way to prevent neural networks from overfitting
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
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Session-based recommendations with recurrent neural networks
B. Hidasi, A. Karatzoglou, L. Baltrunas, and D. Tikk · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
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Collaborative deep learning for recommender systems
H. Wang, N. Wang, and D.-Y. Yeung · 2015
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N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
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Sequential click prediction for sponsored search with recurrent neural networks
Y. Zhang, H. Dai, C. Xu, J. Feng, T. Wang, J. Bian, B. Wang, and T.-Y. Liu · 2014
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Deep speech 2: End-to-end speech recognition in english and mandarin
Baidu Research · 2015
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Artificial neural networks applied to taxi destination prediction
A. de Brébisson, É. Simon, A. Auvolat, P. Vincent, and Y. Bengio · 2015
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Distilling the knowledge in a neural network
H. Geoffrey, V. Oriol, and D. Jeff · 2015
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Y. Gal · 2016
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Unifying distillation and privileged information
D. Lopez-Paz, B. Schölkopf, L. Bottou, and V. Vapnik · 2016
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Theano: A Python framework for fast computation of mathematical expressions
Theano Development Team · 2016
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Simple and efficient learning using privileged information
X. Xu, J. T. Zhou, I. W. Tsang, Z. Qin, R. S. M. Goh, and Y. Liu · 2016
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Transfer hashing with privileged information
J. T. Zhou, X. Xu, S. J. Pan, I. W. Tsang, Z. Qin, and R. S. M. Goh · 2016
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