@Article{JCM-21-339,
author = {Huang , Si-Ming},
title = {The Primal-Dual Potential Reduction Algorithm for Positive Semi-Definite Programming},
journal = {Journal of Computational Mathematics},
year = {2003},
volume = {21},
number = {3},
pages = {339--346},
abstract = {<p style="text-align: justify;">In this paper we introduce a primal-dual potential reduction algorithm for positive semi-definite programming. Using the symetric preserving scalings for both primal and dual interior matrices, we can construct an algorithm which is very similar to the primal-dual potential reduction algorithm of Huang and Kortanek [6] for linear programming. The complexity of the algorithm is either $O(n \log(X^0\cdot S^0/\epsilon))$ or $O(\sqrt{n}\log(X^0\cdot S^0/\epsilon))$ depends on the value of $\rho$ in the primal-dual potential function, where $X^0$ and $S^0$ is the initial interior matrices of the positive semi-definite programming.</p>},
issn = {1991-7139},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jcm/10262.html}
}