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Derivative-free optimization (sometimes referred to as blackbox optimization) is a discipline in mathematical optimization that does not use derivative information in the classical sense to find optimal solutions: Sometimes information about the derivative of the objective function f is unavailable, unreliable or impractical to obtain. For example, f…
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Derivative-free optimization | related to Algorithms | Notable | 0.60 | section |
| Derivative-free optimization | related to Algorithms | Bayesian | 0.60 | section |
| Derivative-free optimization | related to Algorithms | Natural | 0.60 | section |
| Derivative-free optimization | related to Algorithms | CMA-ES | 0.60 | section |
| Derivative-free optimization | related to Algorithms | SNES | 0.60 | section |
| Derivative-free optimization | related to Algorithms | Genetic | 0.60 | section |
| Derivative-free optimization | related to Algorithms | Mead | 0.60 | section |
| Derivative-free optimization | related to Algorithms | COBYLA | 0.60 | section |
| Derivative-free optimization | related to Algorithms | PRIMA | 0.60 | section |
| Derivative-free optimization | related to Algorithms | Random | 0.60 | section |
| Derivative-free optimization | related to Algorithms | Luus | 0.60 | section |
| Derivative-free optimization | related to Algorithms | Jaakola | 0.60 | section |
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