A parallel approximation algorithm for mixed packing and covering semidefinite programs
Data Structures and Algorithms
2012-01-31 v1 Distributed, Parallel, and Cluster Computing
Abstract
We present a parallel approximation algorithm for a class of mixed packing and covering semidefinite programs which generalize on the class of positive semidefinite programs as considered by Jain and Yao [2011]. As a corollary we get a faster approximation algorithm for positive semidefinite programs with better dependence of the parallel running time on the approximation factor, as compared to that of Jain and Yao [2011]. Our algorithm and analysis is on similar lines as that of Young [2001] who considered analogous linear programs.
Cite
@article{arxiv.1201.6090,
title = {A parallel approximation algorithm for mixed packing and covering semidefinite programs},
author = {Rahul Jain and Penghui Yao},
journal= {arXiv preprint arXiv:1201.6090},
year = {2012}
}
Comments
8 pages, version 1