Kernel function based interior-point algorithms for semidefinite optimization
نویسندگان
چکیده
منابع مشابه
Kernel Function Based Interior–point Algorithms for Semidefinite Optimization
We propose a primal-dual interior-point algorithm for semidefinite optimization(SDO) based on a class of kernel functions which are both eligible and self-regular. New search directions and proximity measures are defined based on these functions. We show that the algorithm has O( √ n log ε ) and O( √ n logn log ε ) complexity results for smalland large-update methods, respectively. These are th...
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ژورنال
عنوان ژورنال: Mathematical Inequalities & Applications
سال: 2013
ISSN: 1331-4343
DOI: 10.7153/mia-16-98