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Multilinear subspace learning

Known as: Multilinear subspace, Tensor subspace learning 
Multilinear subspace learning is an approach to dimensionality reduction. Dimensionality reduction can be performed on data tensor whose observations… 
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Related topics

Related topics

30 relations
Artificial neural networkBig dataComputer data storageCurse of dimensionality

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
A geometric approach to study p-summability in multilinear mappings
We prove that the equivalences between the local definition, the Pietsch's Domination theorem and the Pietsch's factorization… 
2016
2016
PARAFAC-based multilinear subspace clustering for tensor data
Subspace clustering has become an increasingly popular data analysis and machine learning method, whose main assumption is that… 
2012
2012
A agonística entre dispositivo de visibilidade e modos de subjetivação no blog da Galera de Capricho
A luz da concepcao foucaulteana, este trabalho vai problematizar o funcionamento de dispositivo de visualidade em blogs juvenis… 
2012
2012
Analysis of the Deflated Conjugate Gradient Method Based on Symmetric Multigrid Theory
Deflation techniques for Krylov subspace methods and in particular the conjugate gradient method have seen a lot of attention in… 
2012
2012
A multilinear generalisation of the Hilbert transform and fractional integration.
We study a multilinear analogue of the Hilbert transform. As can be expected, the finiteness of the form depends on cancellation… 
2009
2009
Head pose estimation using multilinear subspace analysis for robot human awareness
Mobile robots, operating in unconstrained indoor and outdoor environments, would benefit in many ways from perception of the… 
2008
2008
Refractory cytopenia with multilinear dysplasia (RCMD) in patient with Fanconi anaemia
2007
2007
Uncorrelated Multilinear Discriminant Analysis with Regularization for Gait Recognition
This paper proposes a novel uncorrelated multilinear discriminant analysis (UMLDA) algorithm for the challenging problem of gait… 
2006
2006
Applying Ensembles of Multilinear Classifiers in the Frequency Domain
Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning… 
2006
2006
A new adaptive control algorithm for systems with multilinear parametrization
Adaptive control of nonlinearly parametrized (NLP) systems is an unknown field, where few results have been proposed up to now…