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Quadratic programming (QP) is the process of solving certain mathematical optimization problems involving quadratic functions. Specifically, one seeks to optimize (minimize or maximize) a multivariate quadratic function subject to linear constraints on the variables. Quadratic programming is a type of nonlinear programming.
Problem formulation, Solution methods & Run-time complexity
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quadratic programming problem constraints problems function linear optimization lagrangian solution program positive definite variables convex matrix one solving specifically constrained
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Quadratic programming | is a | type of nonlinear programming | 0.90 | text |
| Quadratic programming | related to Constrained least squares | As | 0.60 | section |
| Quadratic programming | related to Constrained least squares | RTR | 0.60 | section |
| Quadratic programming | related to Constrained least squares | Cholesky | 0.60 | section |
| Quadratic programming | related to Constrained least squares | RT | 0.60 | section |
| Quadratic programming | related to Constrained least squares | Conversely | 0.60 | section |
| Quadratic programming | related to Convex quadratic programming | For | 0.60 | section |
| Quadratic programming | related to Convex quadratic programming | Hence | 0.60 | section |
| Quadratic programming | related to Convex quadratic programming | This | 0.60 | section |
| Quadratic programming | related to Convex quadratic programming | Kozlov | 0.60 | section |
| Quadratic programming | related to Convex quadratic programming | Tarasov | 0.60 | section |
| Quadratic programming | related to Convex quadratic programming | Khachiyan | 0.60 | section |
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