Results 281 to 290 of about 280,565 (313)
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2010
In many modern applications involving large data sets, statisticians are confronted with a large m×n matrix X = (x ij) that encodes n features on each of mobjects. For instance, in gene microarray studies x ij represents the expression level of the ith gene under the jth experimental condition [13].
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In many modern applications involving large data sets, statisticians are confronted with a large m×n matrix X = (x ij) that encodes n features on each of mobjects. For instance, in gene microarray studies x ij represents the expression level of the ith gene under the jth experimental condition [13].
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1993
In this chapter we discuss reduction of matrices to the canonical form by use of orthogonal transformations in the spaces of images and preimages. Such canonical form is called the singular value decomposition. In what follows we will use the well-known polar decomposition, which is recalled in Section 1 in course of discussion of singular value ...
S. K. Godunov +3 more
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In this chapter we discuss reduction of matrices to the canonical form by use of orthogonal transformations in the spaces of images and preimages. Such canonical form is called the singular value decomposition. In what follows we will use the well-known polar decomposition, which is recalled in Section 1 in course of discussion of singular value ...
S. K. Godunov +3 more
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Downdating the Singular Value Decomposition
SIAM Journal on Matrix Analysis and Applications, 1995Let \(A\) be a matrix with known singular values and left and/or right singular vectors, and let \(A'\) be the matrix obtained by deleting a row from \(A\). Computing the singular value decomposition (SVD) of \(A'\) from the SVD of \(A\) is called the downdating singular value decomposition problem (DSVDP).
Gu, Ming, Eisenstat, Stanley C.
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Continuation of Singular Value Decompositions
Mediterranean Journal of Mathematics, 2005In this work we consider computing a smooth path for a (block) singular value decomposition of a full rank matrix valued function. We give new theoretical results and then introduce and implement several algorithms to compute a smooth path. We illustrate performance of the algorithms with a few numerical examples.
L. DIECI L +2 more
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Generalizing the Singular Value Decomposition
SIAM Journal on Numerical Analysis, 1976Two generalizations of the singular value decomposition are given. These generalizations provided a unified way of regarding certain matrix problems and the numerical techniques which are used to s...
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Functional Tensor Singular Value Decomposition
SIAM Journal on Scientific ComputingzbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chuan Wang +4 more
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