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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.
2015
2015
Classification of Multi-Frequency Polarimetric SAR Images Based on Multi-Linear Subspace Learning of Tensor Objects
One key problem for the classification of multi-frequency polarimetric SAR images is to extract target features simultaneously in… 
2011
2011
TENSOR NORMS RELATED TO THE SPACE OF COHEN p-NUCLEAR MULTILINEAR MAPPINGS
In this paper we consider the ideal of Cohen p-nuclear multilinear mappings, which is a natural multilinear extension of the… 
2009
2009
Multilinear Subspace Learning for Face and Gait Recognition
Face and gait recognition problems are challenging due to largely varying appearances, highly complex pattern distributions, and… 
2009
2009
Age determination of humpback whales Megaptera novaeangliae through blubber fatty acid compositions of biopsy samples
The ability to determine the age of individual humpback whales Megaptera novaeangliae and estimate population age distributions… 
2008
2008
Face Recognition by Discriminative Orthogonal Rank-one Tensor Decomposition
Discriminative subspace analysis has been a popular approach to face recognition. Most of the previous work such as Eigen-faces… 
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
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… 
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… 
2005
2005
Yet another subspace tracker
The paper introduces a new algorithm for tracking the dominant subspace of the correlation matrix associated with time series… 
1997
1997
A Bernstein–Markov Theorem for Normed Spaces
Abstract LetXandYbe real normed linear spaces and let φ:X →  R be a non-negative function satisfying φ(x + y) ≤ φ(x) + ‖y‖ for… 
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