Approximating Semidefinite Packing Programs

In this paper we define semidefinite packing programs and describe an algorithm to approximately solve these problems. Semidefinite packing programs arise in many applications such as semidefinite programming relaxations for combinatorial optimization problems, sparse principal component analysis, and sparse variance unfolding techniques for dimension reduction. Our algorithm exploits the structural similarity between semidefinite packing programs and linear packing programs. Key words. semidefinite programming, combinatorial optimization, approximation algorithms, primal-dual methods, nonsmooth optimization AMS subject classifications. 90C22, 49M29 DOI. 10.1137/090762671

• Type: Journal
• Year: 2011
• Where: SIAMJO
• Authors: Garud Iyengar, David J. Phillips, Clifford Stein
• Keywords: Combinatorial Optimization, Combinatorial Optimization Problems, Semidefinite Packing Programs, SIAMJO 2011, Software Engineering