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Recurrent Neural Networks (RNNs) are very successful at solving challenging problems with sequential data.
Analysis of individual differences in multidimensional scaling via an N-way generalization of “Eckart-Young” decomposition
J Douglas Carroll and Jih-Jie Chang · 1970
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Foundations of the PARAFAC procedure: Models and conditions for an ”explanatory” multimodal factor analysis
Richard A Harshman · 1970
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Networks and the best approximation property
Federico Girosi and Tomaso Poggio · 1990
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Handwritten digit recognition with a back-propagation network
Yann LeCun, Bernhard E Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne E Hubbard, and Lawrence D Jackel · 1990
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Learning to forget: Continual prediction with LSTM
Felix A Gers, Jürgen Schmidhuber, and Fred Cummins · 1999
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Multilinear analysis of image ensembles: Tensorfaces
M Alex O Vasilescu and Demetri Terzopoulos · 2002
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Tensor decompositions and applications
Tamara G Kolda and Brett W Bader · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Hierarchical singular value decomposition of tensors
Lars Grasedyck · 2010
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Tomáš Mikolov, Stefan Kombrink, Lukáš Burget, Jan Černockỳ, and Sanjeev Khudanpur · 2011
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Tensor-train decomposition
Ivan V Oseledets · 2011
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Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton · 2013
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Tensorizing neural networks
Alexander Novikov, Dmitrii Podoprikhin, Anton Osokin, and Dmitry P Vetrov · 2015
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On multiplicative integration with recurrent neural networks
Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, and Ruslan R Salakhutdinov · 2016
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Word embeddings via tensor factorization
Eric Bailey and Shuchin Aeron · 2017
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Tensor networks for dimensionality reduction and large-scale optimization: Part 2 applications and future perspectives
Andrzej Cichocki, Anh-Huy Phan, Qibin Zhao, Namgil Lee, Ivan Oseledets, Masashi Sugiyama, Danilo P Mandic, et al · 2017
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Tensor methods and recommender systems
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Tensor-train recurrent neural networks for video classification
Yinchong Yang, Denis Krompass, and Volker Tresp · 2017
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Convolutional rectifier networks as generalized tensor decompositions
Nadav Cohen and Amnon Shashua · 2016
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Long-term forecasting using tensor-train RNNs
Rose Yu, Stephan Zheng, Anima Anandkumar, and Yisong Yue · 2017
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Boosting dilated convolutional networks with mixed tensor decompositions
Nadav Cohen, Ronen Tamari, and Amnon Shashua · 2018
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Valentin Khrulkov, Alexander Novikov, and Ivan Oseledets · 2018
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