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Abstract: . A central drawback of primal-dual interior point methods for semidefinite programs is their lack of ability to exploit problem structure in cost and coefficient matrices. This restricts applicability to problems of small dimension. Typically semidefinite relaxations arising in combinatorial applications have sparse and well structured cost and coefficient matrices of huge order. We present a method that allows to compute acceptable approximations to the optimal solution of large problems... (Update)
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BibTeX entry: (Update)
C. Helmberg and F. Rendl. A spectral bundle method for semidefinite programming. Technical Report SC-97-37, Konrad-Zuse-Zentrum fuer Informationstechnik, Berlin, August 1997. Revised: October 1997. http://citeseer.ist.psu.edu/article/helmberg97spectral.html More
@article{ helmberg00spectral,
author = "C. Helmberg and F. Rendl",
title = "A spectral bundle method for semidefinite programming",
journal = "SIAM Journal on Optimization",
volume = "10(3)",
pages = "673--696",
year = "2000",
url = "citeseer.ist.psu.edu/article/helmberg97spectral.html" }
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