Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Practical Inexact Proximal Quasi-Newton Method with Global Complexity
  Analysis   Recently several methods were proposed for sparse optimization which make
careful use of second-order information [10, 28, 16, 3] to improve local
convergence rates. These methods construct a composite quadratic approximation
using Hessian information, optimize this approximation using a first-order
method, such as coordinate descent and employ a line search to ensure
sufficient descent. Here we propose a general framework, which includes
slightly modified versions of existing algorithms and also a new algorithm,
which uses limited memory BFGS Hessian approximations, and provide a novel
global convergence rate analysis, which covers methods that solve subproblems
via coordinate descent.

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The categories of this paper are: solv-int
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The categories of this paper are: eess
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The categories of this paper are: hep-th
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The categories of this paper are: gr-qc
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The categories of this paper are: nlin
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The categories of this paper are: q-bio
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The categories of this paper are: mtrl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: plasm-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci
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The categories of this paper are: nucl-ex
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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: quant-ph