About: Multilinear subspace learning

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Multilinear subspace learning is an approach to dimensionality reduction. Dimensionality reduction can be performed on a data tensor whose observations have been vectorized and organized into a data tensor, or whose observations are matrices that are concatenated into a data tensor. Here are some examples of data tensors whose observations are vectorized or whose observations are matrices concatenated into data tensor images (2D/3D), video sequences (3D/4D), and hyperspectral cubes (3D/4D).

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rdfs:label	Multilinear subspace learning (en)
rdfs:comment	Multilinear subspace learning is an approach to dimensionality reduction. Dimensionality reduction can be performed on a data tensor whose observations have been vectorized and organized into a data tensor, or whose observations are matrices that are concatenated into a data tensor. Here are some examples of data tensors whose observations are vectorized or whose observations are matrices concatenated into data tensor images (2D/3D), video sequences (3D/4D), and hyperspectral cubes (3D/4D). (en)
foaf:depiction
dcterms:subject	Machine learning Multilinear algebra Tensors Dimension reduction
Wikipage page ID	30909817 (xsd:integer)
Wikipage revision ID	1005594408 (xsd:integer)
Link from a Wikipage to another Wikipage	Sandia National Laboratories Demetri Terzopoulos Vector space Independent component analysis Multilinear algebra Coordinate vector Linear mapping Computer data storage Machine learning Data acquisition Linear discriminant analysis Linear subspace Local optimum Multilinear algebra Principal component analysis Dimension reduction Tensor Tensor software Hyperspectral imaging Tensors Big data Higher-order singular value decomposition Tucker decomposition Dimension reduction Canonical correlation CP decomposition Canonical correlation analysis Multilinear principal component analysis Video Image Multilinear PCA Multilinear subspace learning PARAFAC Tensor decomposition High-dimensional High-dimensional data High-dimensional vector space dbr:Multilinear_independent_component_analysis
Link from a Wikipage to an external page	http://www.dsp.utoronto.ca/~haiping/CodeData/USFGait17_32x22x10.zip http://www.mathworks.fr/matlabcentral/fileexchange/35782 https://dx.doi.org/10.1016/j.patcog.2011.01.004 https://web.archive.org/web/20110717172720/http:/csmr.ca.sandia.gov/~tgkolda/TensorToolbox/ http://www.dsp.utoronto.ca/~haiping/CodeData/USFGait17_128x88x20.zip http://www.dsp.utoronto.ca/~haiping/CodeData/USFGait17_64x44x20.zip http://www.dsp.utoronto.ca/~haiping/Publication/SurveyMSL_PR2011.pdf http://www.mathworks.com/matlabcentral/fileexchange/26168 http://www.mathworks.com/matlabcentral/fileexchange/35432 http://videolectures.net/icml08_lu_ump/
sameAs	Multilinear subspace learning Multilinear subspace learning Multilinear subspace learning Multilinear subspace learning
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has abstract	Multilinear subspace learning is an approach to dimensionality reduction. Dimensionality reduction can be performed on a data tensor whose observations have been vectorized and organized into a data tensor, or whose observations are matrices that are concatenated into a data tensor. Here are some examples of data tensors whose observations are vectorized or whose observations are matrices concatenated into data tensor images (2D/3D), video sequences (3D/4D), and hyperspectral cubes (3D/4D). The mapping from a high-dimensional vector space to a set of lower dimensional vector spaces is a multilinear projection. When observations are retained in the same organizational structure as the sensor provides them; as matrices or higher order tensors, their representations are computed by performing N multiple linear projections. Multilinear subspace learning algorithms are higher-order generalizations of linear subspace learning methods such as principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA) and canonical correlation analysis (CCA). (en)
prov:wasDerivedFrom	wikipedia-en:Multilinear_subspace_learning?oldid=1005594408&ns=0
page length (characters) of wiki page	17359 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Multilinear_subspace_learning
is Link from a Wikipage to another Wikipage of	Neural network Non-negative matrix factorization Curse of dimensionality Empirical orthogonal functions Multilinear algebra Machine learning Singular value decomposition Sufficient dimension reduction Data analysis Data mining Gait analysis Linear subspace Locality-sensitive hashing Anastasios Venetsanopoulos Facial recognition system Dimensionality reduction Principal component analysis Tensor Tensor software

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