publication . Preprint . 2017

Deep Learning with Dynamic Computation Graphs

Looks, Moshe; Herreshoff, Marcello; Hutchins, DeLesley; Norvig, Peter;
Open Access English
  • Published: 07 Feb 2017
Abstract
Comment: Published as a conference paper at ICLR 2017
Subjects
free text keywords: Computer Science - Neural and Evolutionary Computing, Computer Science - Learning, Statistics - Machine Learning
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Martın Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. arXiv, 1603.04467, 2016.

Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein. Learning to compose neural networks for question answering. In NAACL, 2016.

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. In ICLR, 2015.

Anna Maria Bianucci, Alessio Micheli, Alessandro Sperduti, and Antonina Starita. Application of cascade correlation networks for structures to chemistry. Applied Intelligence, 2000.

Samuel R. Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D. Manning, and Christopher Potts. A fast unified model for parsing and sentence understanding. In NAACL, 2016.

Ronan Collobert, Koray Kavukcuoglu, and Cle´ment Farabet. Torch7: A Matlab-like environment for machine learning. In BigLearn, NIPS Workshop, 2011.

Christoph Goller and Andreas Kuchler. Learning task-dependent distributed representations by backpropagation through structure. In ICNN, 1996.

John Hughes. Generalising monads to arrows. Science of Computer Programming, 2000.

Graham Hutton and Erik Meijer. Monadic parser combinators. Technical Report NOTTCS-TR-96-4, 1996. [OpenAIRE]

Steven Kearnes, Kevin McCloskey, Marc Berndl, Vijay Pande, and Patrick Riley. Molecular graph convolutions: moving beyond fingerprints. Journal of Computer-Aided Molecular Design, 2016. [OpenAIRE]

Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.

Jiwei Li, Minh-Thang Luong, Dan Jurafsky, and Eudard Hovy. When are tree structures necessary for deep learning of representations? arXiv, 1503.00185, 2015.

Tsendsuren Munkhdalai and Hong Yu. Neural semantic encoders. arXiv, 1607.04315, 2016a. [OpenAIRE]

Tsendsuren Munkhdalai and Hong Yu. 1607.04492, 2016b.

Abstract
Comment: Published as a conference paper at ICLR 2017
Subjects
free text keywords: Computer Science - Neural and Evolutionary Computing, Computer Science - Learning, Statistics - Machine Learning
Download from

Martın Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. arXiv, 1603.04467, 2016.

Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein. Learning to compose neural networks for question answering. In NAACL, 2016.

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. In ICLR, 2015.

Anna Maria Bianucci, Alessio Micheli, Alessandro Sperduti, and Antonina Starita. Application of cascade correlation networks for structures to chemistry. Applied Intelligence, 2000.

Samuel R. Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D. Manning, and Christopher Potts. A fast unified model for parsing and sentence understanding. In NAACL, 2016.

Ronan Collobert, Koray Kavukcuoglu, and Cle´ment Farabet. Torch7: A Matlab-like environment for machine learning. In BigLearn, NIPS Workshop, 2011.

Christoph Goller and Andreas Kuchler. Learning task-dependent distributed representations by backpropagation through structure. In ICNN, 1996.

John Hughes. Generalising monads to arrows. Science of Computer Programming, 2000.

Graham Hutton and Erik Meijer. Monadic parser combinators. Technical Report NOTTCS-TR-96-4, 1996. [OpenAIRE]

Steven Kearnes, Kevin McCloskey, Marc Berndl, Vijay Pande, and Patrick Riley. Molecular graph convolutions: moving beyond fingerprints. Journal of Computer-Aided Molecular Design, 2016. [OpenAIRE]

Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.

Jiwei Li, Minh-Thang Luong, Dan Jurafsky, and Eudard Hovy. When are tree structures necessary for deep learning of representations? arXiv, 1503.00185, 2015.

Tsendsuren Munkhdalai and Hong Yu. Neural semantic encoders. arXiv, 1607.04315, 2016a. [OpenAIRE]

Tsendsuren Munkhdalai and Hong Yu. 1607.04492, 2016b.

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