For linear semidefinite programming some advances by dealing with degeneracy and the semidefinite facial reduction are discussed. Two relatively recent areas of application are presented. Finally a ...

A lower bound is computed on a semidefinite relaxation of the constraint system and the objective function. Numerical results are presented using the SDPA (SemiDefinite Programming Algorithm), solver ...

Polynomial optimization problem solver. Uses relaxation to convert the problem into Semidefinite programming. Can be also used just as Semidefinite programming solver ...

Srijuntongsiri, G. , & Vavasis, S. . (2004). A Fully Sparse Implementation of a Primal- Dual Interior-Point Potential Reduction Method for Semidefinite Programming.

In the presence of symmetry, the semidefinite program simplifies considerably, becoming a linear program in the case of isotropic and Werner states. Using these techniques, we determine the p.p.t.

Many clustering problems can be solved using semidefinite programming. Theoretical results in this vein frequently consider data with a planted clustering and a notion of signal strength such that the ...

Semidefinite programming relaxations offer a powerful method to construct such relaxations. In many instances it was observed that a semidefinite relaxation becomes very accurate when the noise level ...

Although semidefinite programming is solvable in polynomial time (26), it tends to be computationally expensive. Javanmard et al. (1) used a low-rank factorization heuristic, proposed over a decade ...

Semidefinite Programming with Homotopy Conditional Gradient Method (HCGM) and Vu-Condat methods for solving two problems: Fashion-MNIST classification using k-means clustering and geometric embedding ...