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In mathematical optimization, a quadratically constrained quadratic program (QCQP) is an optimization problem in which both the objective function and the constraints are quadratic functions. It has the form
Relaxation, Hardness & Example
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problem qcqp semidefinite programming quadratic pm constraints convex optimization matrices program p0 general relaxations sdp constrained positive np-hard relaxation linear
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| photolithography | instance of | and SDP relaxation of the dual provides good lower bounds.QCQP is used to finely tune machine setting in high-precision applications | 0.80 | text |
| Quadratically constrained quadratic program | related to Hardness | QCQP | 0.60 | section |
| Quadratically constrained quadratic program | related to Hardness | Solving | 0.60 | section |
| Quadratically constrained quadratic program | related to Hardness | NP-hard | 0.60 | section |
| Quadratically constrained quadratic program | related to Hardness | To | 0.60 | section |
| Quadratically constrained quadratic program | related to Hardness | Hence | 0.60 | section |
| Quadratically constrained quadratic program | related to Hardness | Since | 0.60 | section |
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