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The paper surveys the topic of tensor decompositions in modern machine learning applications.
Some mathematical notes on three-mode factor analysis
Ledyard R Tucker · 1966
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A general framework for adaptive processing of data structures
Paolo Frasconi, Marco Gori, and Alessandro Sperduti · 1998
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Towards a standardized notation and terminology in multiway analysis
Henk A. L. Kiers · 2000
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Tensor Decompositions and Applications
Tamara G. Kolda and Brett W. Bader · 2009
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Tensor-Train Decomposition
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Temporal link prediction using matrix and tensor factorizations
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A three-way model for collective learning on multi-relational data
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Compositional Generative Mapping for Tree-Structured Data - Part I: Bottom-Up Probabilistic Modeling of Trees
Davide Bacciu, Alessio Micheli, and Alessandro Sperduti · 2012
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An input-output hidden Markov model for tree transductions
Davide Bacciu, Alessio Micheli, and Alessandro Sperduti · 2013
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Compositional Generative Mapping for Tree-Structured Data - Part II: Topographic Projection Model
Davide Bacciu, Alessio Micheli, and Alessandro Sperduti · 2013
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Recursive deep models for semantic compositionality over a sentiment treebank (RNTN)
Richard Socher, Alex Perelygin, and Jy Wu · 2013
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Spotting misbehaviors in location-based social networks using tensors
Evangelos Papalexakis, Konstantinos Pelechrinis, and Christos Faloutsos · 2014
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Tensor decompositions for signal processing applications: From two-way to multiway component analysis
Andrzej Cichocki, Danilo Mandic, Lieven De Lathauwer, Guoxu Zhou, Qibin Zhao, Cesar Caiafa, and Huy Anh Phan · 2015
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Speeding-up convolutional neural networks using fine-tuned cp-decomposition
Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba, Ivan V. Oseledets, and Victor S. Lempitsky · 2015
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Tensorizing neural networks
Alexander Novikov, Dmitrii Podoprikhin, Anton Osokin, and Dmitry P Vetrov · 2015
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Inferring relations in knowledge graphs with tensor decompositions
A. Padia, K. Kalpakis, and T. Finin · 2016
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scikit-tensor
Maximilian Nickel and Evert Rol · 2016
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Andrzej Cichocki, Anh Huy Phan, Qibin Zhao, Namgil Lee, Ivan Oseledets, Masashi Sugiyama, and Danilo Mandic · 2017
Tensord: A tensor decomposition library in tensorflow
Liyang Hao, Siqi Liang, Jinmian Ye, and Zenglin Xu · 2018
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Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models
Daniele Castellana and Davide Bacciu · 2019
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A survey on tensor techniques and applications in machine learning
Y. Ji, Q. Wang, X. Li, and J. Liu · 2019
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Tucker tensor layer in fully connected neural networks
Giuseppe Giovanni Calvi, Ahmad Moniri, Mahmoud Mahfouz, Zeyang Yu, Qibin Zhao, and Danilo P. Mandic · 2019
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A gentle introduction to deep learning for graphs, 2019
Davide Bacciu, Federico Errica, Alessio Micheli, and Marco Podda · 2019
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How powerful are graph neural networks?
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Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks
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Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2019
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Tensorly: Tensor learning in python
Jean Kossaifi, Yannis Panagakis, Anima Anandkumar, and Maja Pantic · 2019
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Mining temporal changes in strengths and weaknesses of cricket players using tensor decomposition
Swarup Ranjan Behera and Vijaya Saradhi · 2020
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Tensor decompositions in recursive neural networks for tree-structured data
Daniele Castellana and Davide Bacciu · 2020
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Generalising recursive neural models by tensor decomposition
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A fair comparison of graph neural networks for graph classification
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Theoretically expressive and edge-aware graph learning
Federico Errica, Davide Bacciu, and Alessio Micheli · 2020
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HOTTBOX: Higher Order Tensors ToolBOX
Ilya Kisil, Giuseppe G. Calvi, Bruno Scalzo Dees, and Danilo P. Mandic · 2020
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