Semidefinite Programming Problems
Semidefinite programming involves the minimization of a linear function subject to the constraint that an affine combination of symmetric matrices is positive semidefinite. Several types of problems can be transformed to this form. This constraint is in general nonlinear and nonsmooth yet convex. Semidefinite programming can be viewed as an extension of linear programming and reduces to the linear programming case when the symmetric matrices are diagonal.
KeywordsLinear Matrix Inequality Positive Semidefinite Semidefinite Programming Diagonal Covariance Matrix Semidefinite Programming Relaxation
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