Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Convergent Gradient Descent Algorithm for Rank Minimization and
  Semidefinite Programming from Random Linear Measurements   We propose a simple, scalable, and fast gradient descent algorithm to
optimize a nonconvex objective for the rank minimization problem and a closely
related family of semidefinite programs. With $O(r^3 \kappa^2 n \log n)$ random
measurements of a positive semidefinite $n \times n$ matrix of rank $r$ and
condition number $\kappa$, our method is guaranteed to converge linearly to the
global optimum.

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The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
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The categories of this paper are: eess
3
The categories of this paper are: physics
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The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
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The categories of this paper are: chem-ph
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The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
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The categories of this paper are: patt-sol
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The categories of this paper are: chao-dyn
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The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: solv-int
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat