Computational Optimization and Applications
A Note on the Calculation of Step-Lengths in Interior-Point Methods for Semidefinite Programming
Computational Optimization and Applications
Solving Hankel matrix approximation problem using semidefinite programming
Journal of Computational and Applied Mathematics
Interior-Point Method for Nuclear Norm Approximation with Application to System Identification
SIAM Journal on Matrix Analysis and Applications
Nonnegative factorization of diffusion tensor images and its applications
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
A large-update primal-dual interior-point method for second-order cone programming
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
An inexact spectral bundle method for convex quadratic semidefinite programming
Computational Optimization and Applications
An efficient multiple-kernel learning for pattern classification
Expert Systems with Applications: An International Journal
A homotopy method for nonlinear semidefinite programming
Computational Optimization and Applications
Journal of Computational and Applied Mathematics
Curvature integrals and iteration complexities in SDP and symmetric cone programs
Computational Optimization and Applications
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We study different choices of search direction for primal-dual interior-point methods for semidefinite programming problems. One particular choice we consider comes from a specialization of a class of algorithms developed by Nesterov and Todd for certain convex programming problems. We discuss how the search directions for the Nesterov--Todd (NT) method can be computed efficiently and demonstrate how they can be viewed as Newton directions. This last observation also leads to convenient computation of accelerated steps, using the Mehrotra predictor-corrector approach, in the NT framework. We also provide an analytical and numerical comparison of several methods using different search directions, and suggest that the method using the NT direction is more robust than alternative methods.