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Abstract
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In this article, we present a new full Nesterov-Todd step infeasible interior-point method
for second-order cone optimization based on a non-coercive kernel function. The main iteration
consists of a so-called feasibility step and one centering step, whereas the earlier versions, in
[4, 21], needed two additional centering steps. We use a kernel function to induce the feasibility
step. The new algorithm reduces the searching steps in each iteration and tenders an interesting
analysis for complexity bound.
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