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Semidefinite programming (SDP) is a subfield of mathematical programming concerned with the optimization of a linear objective function (a user-specified function that the user wants to minimize or maximize) over the intersection of the cone of positive semidefinite matrices with an affine space, i.e., a spectrahedron.
Examples, Motivation and definition & Algorithms for solving SDPs
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displaystyle sdp semidefinite problem programming sdps optimization matrix linear problems algorithms method matrices program used approximate dual variables vectors constraints
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Semidefinite programming | is a | relatively new field of optimization which is of growing interest for several reasons | 0.90 | text |
| Semidefinite programming | has application | Semidefinite | 0.60 | section |
| Semidefinite programming | has application | SDPs | 0.60 | section |
| Semidefinite programming | has application | LMIs | 0.60 | section |
| Semidefinite programming | has application | It | 0.60 | section |
| Semidefinite programming | related to External links | Links | 0.60 | section |
| Semidefinite programming | related to External links | László Lovász | 0.60 | section |
| Semidefinite programming | related to Initial motivation | In | 0.60 | section |
| Semidefinite programming | related to Initial motivation | LP | 0.60 | section |
| Semidefinite programming | related to Initial motivation | SDP | 0.60 | section |
| Semidefinite programming | related to Initial motivation | Specifically | 0.60 | section |
| Semidefinite programming | related to References | Lieven Vandenberghe | 0.60 | section |
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