In this work, we propose a primal-dual interior-point algorithm for semidefinite optimization based on a new kernel function with an efficient logarithmic barrier term. We show that the best result of iteration bounds can be achieved, namely
for large update and
for small-update methods.
Key Words: Semidefinite optimization, kernel functions, primal-dual interior-point method, large and small-update methods, complexity bound.
2010 Mathematics Subject Classification: Primary 90C22; Secondary 30C40, 90C51.
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