Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Scatter Matrix Concordance: A Diagnostic for Regressions on Subsets of
  Data   Linear regression models depend directly on the design matrix and its
properties. Techniques that efficiently estimate model coefficients by
partitioning rows of the design matrix are increasingly popular for large-scale
problems because they fit well with modern parallel computing architectures. We
propose a simple measure of {\em concordance} between a design matrix and a
subset of its rows that estimates how well a subset captures the
variance-covariance structure of a larger data set. We illustrate the use of
this measure in a heuristic method for selecting row partition sizes that
balance statistical and computational efficiency goals in real-world problems.

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The categories of this paper are: funct-an
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-th
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The categories of this paper are: solv-int
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The categories of this paper are: comp-gas
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The categories of this paper are: astro-ph
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The categories of this paper are: math-ph
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The categories of this paper are: supr-con
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The categories of this paper are: q-fin
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The categories of this paper are: dg-ga
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The categories of this paper are: math
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The categories of this paper are: quant-ph
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The categories of this paper are: physics
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The categories of this paper are: acc-phys
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The categories of this paper are: patt-sol
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The categories of this paper are: eess