On the Nesterov-Todd direction in semidefinite programming
Michael Todd, Kim Toh, and Reha Tutuncu
Nesterov and Todd discuss several path-following
and potential-reduction interior-point methods for
certain convex programming problems. In the special
case of semidefinite programming, we discuss how to
compute the corresponding directions efficiently,
how to view them as Newton directions, and how
to take Mehrotra predictor-corrector steps in this framework.
We also provide some computational results suggesting that
our algorithm provides higher accuracy than alternative methods.
Technical Report 1154, School of Operations Research and Industrial
Engineering, Cornell University, Ithaca, NY.