Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Updating Singular Value Decomposition for Rank One Matrix Perturbation   An efficient Singular Value Decomposition (SVD) algorithm is an important
tool for distributed and streaming computation in big data problems. It is
observed that update of singular vectors of a rank-1 perturbed matrix is
similar to a Cauchy matrix-vector product. With this observation, in this
paper, we present an efficient method for updating Singular Value Decomposition
of rank-1 perturbed matrix in $O(n^2 \ \text{log}(\frac{1}{\epsilon}))$ time.
The method uses Fast Multipole Method (FMM) for updating singular vectors in
$O(n \ \text{log} (\frac{1}{\epsilon}))$ time, where $\epsilon$ is the
precision of computation.

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The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
3
The categories of this paper are: physics
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th
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The categories of this paper are: hep-th
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
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The categories of this paper are: astro-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: chao-dyn
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The categories of this paper are: comp-gas