On adaptive-step primal-dual interior-point algorithms for linear programming
Mathematics of Operations Research
Self-scaled barriers and interior-point methods for convex programming
Mathematics of Operations Research
Determinant Maximization with Linear Matrix Inequality Constraints
SIAM Journal on Matrix Analysis and Applications
Computational Optimization and Applications
Primal-Dual Interior-Point Methods for Self-Scaled Cones
SIAM Journal on Optimization
SIAM Journal on Optimization
On a commutative class of search directions for linear programming over symmetric cones
Journal of Optimization Theory and Applications
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Weighted determinant maximization with linear matrix inequality constraints (maxdet-problem) is a generalization of the semidefinite programming. We give a polynomial-time complexity analysis for the path-following interior-point short-step and predictor-corrector methods for the maxdet-problem based on symmetric Newton equations for certain classes of scaling matrices.