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Automated tight Lyapunov analysis for first-order methods. [PDF]
Math ProgramUpadhyaya M +3 more
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SIAM Review, 1996
In semidefinite programming, one minimizes a linear function subject to the constraint that an affine combination of symmetric matrices is positive semidefinite. Such a constraint is nonlinear and nonsmooth, but convex, so semidefinite programs are convex optimization problems. Semidefinite programming unifies several standard problems (e.g.
Vandenberghe, Lieven, Boyd, Stephen
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In semidefinite programming, one minimizes a linear function subject to the constraint that an affine combination of symmetric matrices is positive semidefinite. Such a constraint is nonlinear and nonsmooth, but convex, so semidefinite programs are convex optimization problems. Semidefinite programming unifies several standard problems (e.g.
Vandenberghe, Lieven, Boyd, Stephen
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European Journal of Operational Research, 2002
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2016
Diese Masterarbeit beschäftigt sich mit dem Thema der semidefiniten Programmierung und ihrer Anwendung im Bereich der Finanzwirtschaft. Es werden die theoretischen Grundlagen der semidefiniten Programmierung und darauf aufbauende Algorithmen vorgestellt. Danach werden verschiedene Anwendungen in der Finanzwirtschaft diskutiert.
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Diese Masterarbeit beschäftigt sich mit dem Thema der semidefiniten Programmierung und ihrer Anwendung im Bereich der Finanzwirtschaft. Es werden die theoretischen Grundlagen der semidefiniten Programmierung und darauf aufbauende Algorithmen vorgestellt. Danach werden verschiedene Anwendungen in der Finanzwirtschaft diskutiert.
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Semidefinite Programming Problems
1999Semidefinite 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.
Christodoulos A. Floudas +8 more
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Semidefinite Programming Relaxation for Nonconvex Quadratic Programs
Journal of Global Optimization, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fujie, Tetsuya, Kojima, Masakazu
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Semidefinite programming and combinatorial optimization
Mathematical Programming, 1997We discuss the use of semidefinite programming for combinatorial optimization problems. The main topics covered include (i) the Lovász theta function and its applications to stable sets, perfect graphs, and coding theory, (ii) the automatic generation of strong valid inequalities, (iii) the maximum cut problem and related problems, and (iv) the ...
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Optimality Conditions in Semidefinite Programming
Numerical Functional Analysis and Optimization, 2014Semidefinite positiveness of operators on Euclidean spaces is characterized. Using this characterization, we compute in a direct way the first-order and second-order tangent sets to the cone of semidefinite positive operators on such a space. These characterizations are useful for optimality conditions in semidefinite programming.
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