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SODA
2010
ACM
216views Algorithms» more  SODA 2010»
14 years 2 months ago
On linear and semidefinite programming relaxations for hypergraph matching
The hypergraph matching problem is to find a largest collection of disjoint hyperedges in a hypergraph. This is a well-studied problem in combinatorial optimization and graph theo...
Yuk Hei Chan, Lap Chi Lau
DAM
2008
111views more  DAM 2008»
13 years 5 months ago
Sums of squares based approximation algorithms for MAX-SAT
We investigate the Semidefinite Programming based Sums of squares (SOS) decomposition method, designed for global optimization of polynomials, in the context of the (Maximum) Sati...
Hans van Maaren, Linda van Norden, M. J. H. Heule
SIAMJO
2008
108views more  SIAMJO 2008»
13 years 5 months ago
Sparse SOS Relaxations for Minimizing Functions that are Summations of Small Polynomials
This paper discusses how to find the global minimum of functions that are summations of small polynomials ("small" means involving a small number of variables). Some spa...
Jiawang Nie, James Demmel
ICASSP
2011
IEEE
12 years 9 months ago
Recovery of sparse perturbations in Least Squares problems
We show that the exact recovery of sparse perturbations on the coefficient matrix in overdetermined Least Squares problems is possible for a large class of perturbation structure...
Mert Pilanci, Orhan Arikan
MP
2006
80views more  MP 2006»
13 years 5 months ago
Minimizing Polynomials via Sum of Squares over the Gradient Ideal
A method is proposed for finding the global minimum of a multivariate polynomial via sum of squares (SOS) relaxation over its gradient variety. That variety consists of all points ...
Jiawang Nie, James Demmel, Bernd Sturmfels