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In this paper, we propose a large-update interior-point algorithm for linear   optimization based on a new kernel function. New search directions and   proximity measure are defined based on this kernel function. We show that if   a strictly feasible starting point is available, then the new algorithm has   O(3/4log n/ε) iteration complexity

A polynomial-time algorithm for linear optimization based on a new kernel function with trigonometric barrier term