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In this paper we propose a primal-dual interior-point algorithm for convex quadratic semidefinite optimization problem. The search direction of algorithm is defined in terms of a matrix function and the iteration is generated by full-Newton step. Furthermore, we derive the iteration bound for the algorithm with small-update method, namely, O( log ), which is best-known bound so far.
@article{RO_2010__44_3_251_0,
author = {Bai, Y. Q. and Wang, F. Y. and Luo, X. W.},
title = {A polynomial-time interior-point algorithm for convex quadratic semidefinite optimization},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {251--265},
publisher = {EDP-Sciences},
volume = {44},
number = {3},
year = {2010},
doi = {10.1051/ro/2010016},
mrnumber = {2762796},
zbl = {1203.90178},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.1051/ro/2010016/}
}
TY - JOUR AU - Bai, Y. Q. AU - Wang, F. Y. AU - Luo, X. W. TI - A polynomial-time interior-point algorithm for convex quadratic semidefinite optimization JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2010 SP - 251 EP - 265 VL - 44 IS - 3 PB - EDP-Sciences UR - http://geodesic.mathdoc.fr/articles/10.1051/ro/2010016/ DO - 10.1051/ro/2010016 LA - en ID - RO_2010__44_3_251_0 ER -
%0 Journal Article %A Bai, Y. Q. %A Wang, F. Y. %A Luo, X. W. %T A polynomial-time interior-point algorithm for convex quadratic semidefinite optimization %J RAIRO - Operations Research - Recherche Opérationnelle %D 2010 %P 251-265 %V 44 %N 3 %I EDP-Sciences %U http://geodesic.mathdoc.fr/articles/10.1051/ro/2010016/ %R 10.1051/ro/2010016 %G en %F RO_2010__44_3_251_0
Bai, Y. Q.; Wang, F. Y.; Luo, X. W. A polynomial-time interior-point algorithm for convex quadratic semidefinite optimization. RAIRO - Operations Research - Recherche Opérationnelle, Tome 44 (2010) no. 3, pp. 251-265. doi: 10.1051/ro/2010016
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