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… (More)
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Papers overview

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Review
2017
Review
2017
Tensors or <italic>multiway arrays</italic> are functions of three or more indices <inline-formula> <tex-math notation="LaTeX… (More)
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2013
2013
Emphasizing essential concepts and system-level perspectives, this book provides a foundation for solving many of today’s most… (More)
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Review
2011
Review
2011
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a… (More)
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2009
2009
This paper proposes an uncorrelated multilinear principal component analysis (UMPCA) algorithm for unsupervised subspace learning… (More)
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2009
2009
Face and gait recognition problems are challenging due to largely varying appearances, highly complex pattern distributions, and… (More)
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Highly Cited
2008
Highly Cited
2008
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects… (More)
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Highly Cited
2007
Highly Cited
2007
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high… (More)
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Highly Cited
2005
Highly Cited
2005
Independent components analysis (ICA) maximizes the statistical independence of the representational components of a training… (More)
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Highly Cited
2005
Highly Cited
2005
Previous work has demonstrated that the image variations of many objects (human faces in particular) under variable lighting can… (More)
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Highly Cited
2003
Highly Cited
2003
Multilinear algebra, the algebra of higher-order tensors, offers a potent mathematical framework for analyzing ensembles of… (More)
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