Singular value decomposition

Known as: SVD, Singular-value decomposition, SV decomposition 
In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix. It is the generalization of the… (More)
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Highly Cited
2010
Highly Cited
2010
We define the hierarchical singular value decomposition (SVD) for tensors of order d ≥ 2. This hierarchical SVD has properties… (More)
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Highly Cited
2007
Highly Cited
2007
The regularized SVD model has O(NK + MK) parameters (N users, M movies, K features). We propose two models with O(MK) parameters… (More)
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Highly Cited
2005
Highly Cited
2005
We study the SVD of an arbitrary matrix , especially its subspaces of activation, which leads in natural manner to pseudoinverse… (More)
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Highly Cited
2004
Highly Cited
2004
We consider the problem of partitioning a set of m points in the n-dimensional Euclidean space into k clusters (usually m and n… (More)
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Highly Cited
2002
Highly Cited
2002
This chapter describes gene expression analysis by Singular Value Decomposition (SVD), emphasizing initial characterization of… (More)
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Highly Cited
2002
Highly Cited
2002
We introduce an incremental singular value decomposition ( SVD) of incomplete data. The SVD is developed as data arrives, and can… (More)
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Highly Cited
2000
Highly Cited
2000
We discuss a multilinear generalization of the singular value decomposition. There is a strong analogy between several properties… (More)
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Highly Cited
1996
Highly Cited
1996
A new approach to low-complexity channel estimation in orthogonal-frequency division multiplexing (OFDM) systems is proposed. A… (More)
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Highly Cited
1995
Highly Cited
1995
This paper introduces singular value decomposition (SVD) algorithms for some standard polynomial computations, in the case where… (More)
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Highly Cited
1993
Highly Cited
1993
In this paper, we present a unified approach to the (related) problems of recovering signal parameters from noisy observations… (More)
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