Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convergence of a Solution Algorithm in Indefinite Quadratic Programming   It is proved that, for an indefinite quadratic programming problem under
linear constraints, any iterative sequence generated by the Proximal DC
decomposition algorithm $R$-linearly converges to a Karush-Kuhn-Tucker point,
provided that the problem has a solution. Another major result of this paper
says that DCA sequences generated by the algorithm converge to a locally unique
solution of the problem if the initial points are taken from a suitably-chosen
neighborhood of it. To deal with the implicitly defined iterative sequences, a
local error bound for affine variational inequalities and novel techniques are
used. Numerical results together with an analysis of the influence of the
decomposition parameter, as well as a comparison between the Proximal DC
decomposition algorithm and the Projection DC decomposition algorithm, are
given in this paper. Our results complement a recent and important paper of Le
Thi, Huynh, and Pham Dinh (J. Optim. Theory Appl. 179 (2018), 103-126).

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The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph