An Empirical Exploration of Recurrent Network Architectures
作者： Ilya Sutskever , Rafal Jozefowicz , Wojciech Zaremba , Wojciech Zaremba
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摘要: Abstract The Recurrent Neural Network (RNN) is an extremely powerful sequence model that is often difficult to train. The Long Short-Term Memory (LSTM) is a specific RNN …
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ai.google 参考文章(25)
Ilya Sutskever, Geoffrey Hinton, James Martens, George Dahl, On the importance of initialization and momentum in deep learning international conference on machine learning. pp. 1139- 1147 ,(2013)
Justin Bayer, Daan Wierstra, Julian Togelius, Jürgen Schmidhuber, Evolving Memory Cell Structures for Sequence Learning international conference on artificial neural networks. pp. 755- 764 ,(2009) , 10.1007/978-3-642-04277-5_76
Tomas Mikolov, Martin Karafiát, Sanjeev Khudanpur, Jan Cernocký, Lukás Burget, Recurrent neural network based language model conference of the international speech communication association. pp. 1045- 1048 ,(2010)
Sepp Hochreiter, Untersuchungen zu dynamischen neuronalen Netzen ,(1991)
James Martens, Deep learning via Hessian-free optimization international conference on machine learning. pp. 735- 742 ,(2010)
Ronan Collobert, Clément Farabet, Koray Kavukcuoglu, Torch7: A Matlab-like Environment for Machine Learning neural information processing systems. ,(2011)
Ilya Sutskever, James Martens, Learning Recurrent Neural Networks with Hessian-Free Optimization international conference on machine learning. pp. 1033- 1040 ,(2011)
Ilya Sutskever, Wojciech Zaremba, Learning to Execute arXiv: Neural and Evolutionary Computing. ,(2014)
Ilya Sutskever, Wojciech Zaremba, Oriol Vinyals, Recurrent Neural Network Regularization arXiv: Neural and Evolutionary Computing. ,(2014)
Mitch Marcus, Beatrice Santorini, Mary Ann Marcinkiewicz, None, Building a large annotated corpus of English: the penn treebank Computational Linguistics. ,vol. 19, pp. 313- 330 ,(1993) , 10.21236/ADA273556