Feasibility issues in a primal-dual interior-point method for linear programming
Mathematical Programming: Series A and B
Self-scaled barriers and interior-point methods for convex programming
Mathematics of Operations Research
Local convergence of predictor-corrector infeasible-interior-point algorithms for SDPs and SDLCPs
Mathematical Programming: Series A and B
Journal of Optimization Theory and Applications
SIAM Journal on Optimization
Primal-Dual Interior-Point Methods for Self-Scaled Cones
SIAM Journal on Optimization
SIAM Journal on Optimization
SIAM Journal on Optimization
Solving Graph Bisection Problems with Semidefinite Programming
INFORMS Journal on Computing
A Full-Newton Step O(n) Infeasible Interior-Point Algorithm for Linear Optimization
SIAM Journal on Optimization
Simplified O(nL) infeasible interior-point algorithm for linear optimization using full-Newton steps
Optimization Methods & Software
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Interior-point methods for semidefinite optimization problems have been studied frequently, due to their polynomial complexity and practical implications. In this paper we propose a primal-dual infeasible interior-point algorithm that uses full Nesterov-Todd (NT) steps with a different feasibility step. We obtain the currently best known iteration bound for semidefinite optimization problems.