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It is a known fact that training recurrent neural networks for tasks that have long term dependencies is challenging.
Learning long-term dependencies with gradient descent is difficult
Yoshua Bengio, Patrice Simard, and Paolo Frasconi · 1994
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Using Fourier-neural recurrent networks to fit sequential input/output data
Renée Koplon and Eduardo D Sontag · 1997
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Forenet: Fourier recurrent networks for time series prediction
Ying-Qian Zhang and Lai-Wan Chan · 2000
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Properties of sums of some elementary functions and modeling of transitional and other processes
Yuri Shestopaloff · 2008
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Sums of exponential functions and their new fundamental properties
Yuri K Shestopaloff · 2010
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Strategies for training large scale neural network language models
Tomáš Mikolov, Anoop Deoras, Daniel Povey, Lukáš Burget, and Jan Černockỳ · 2011
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Nearly optimal sparse Fourier transform
Haitham Hassanieh, Piotr Indyk, Dina Katabi, and Eric Price · 2012
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Simple and practical algorithm for sparse Fourier transform
Haitham Hassanieh, Piotr Indyk, Dina Katabi, and Eric Price · 2012
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Statistical language models based on neural networks
Tomáš Mikolov · 2012
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On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio · 2013
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Eric C Price · 2013
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On the properties of neural machine translation: Encoder-decoder approaches
Kyunghyun Cho, Bart Van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio · 2014
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Sample-optimal Fourier sampling in any constant dimension
Piotr Indyk and Michael Kapralov · 2014
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(Nearly) Sample-optimal sparse Fourier transform
Piotr Indyk, Michael Kapralov, and Eric Price · 2014
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A robust sparse Fourier transform in the continuous setting
Eric Price and Zhao Song · 2015
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
Mart \́mathbf{i} · 2016
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Unitary evolution recurrent neural networks
Martin Arjovsky, Amar Shah, and Yoshua Bengio · 2016
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Fourier-sparse interpolation without a frequency gap
Xue Chen, Daniel M Kane, Eric Price, and Zhao Song · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Nitish Srivastava, Geoffrey E Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Quoc V Le, Navdeep Jaitly, and Geoffrey E Hinton · 2015
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Yu Zhang, Guoguo Chen, Dong Yu, Kaisheng Yaco, Sanjeev Khudanpur, and James Glass · 2016
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Residual lstm: Design of a deep recurrent architecture for distant speech recognition
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The statistical recurrent unit
Junier B Oliva, Barnabás Póczos, and Jeff Schneider · 2017
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Harry Pratt, Bryan Williams, Frans Coenen, and Yalin Zheng · 2017
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