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Rank-Two Relaxation Heuristics for Max-Cut and Other Binary Quadratic Programs
Semidefinite relaxation for certain discrete optimization problems involves replacing a vector-valued variable by a matrix-valued one, producing a convex program while increasing the number of variables by an order of ...
A Computational Study of a Gradient-Based Log-Barrier Algorithm for a Class of Large-Scale SDPs
The authors of this paper recently introduced a transformation that converts a class of semidefinite programs (SDPs) into nonlinear optimization problems free of matrix-valued constraints and variables. This transformation ...
Maximum Stable Set Formulations and Heuristics Based on Continuous Optimization
The stability number for a given graph G is the size of a maximum stable set in G. The Lovasz theta number provides an upper bound on the stability number and can be computed as the optimal value of the Lovasz semidefinite ...