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Graduated optimization is a global optimization technique that attempts to solve a difficult optimization problem by initially solving a greatly simplified problem, and progressively transforming that problem (while optimizing) until it is equivalent to the difficult optimization problem.
Some examples, Technique description & Related optimization techniques
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optimization graduated problem sequence conditions difficult hill point used global optimizing technique problems first convex solution starting find image within
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Graduated optimization | is a | global optimization technique that attempts to solve a difficult optimization problem by initially solving a greatly simplified problem | 0.90 | text |
| Graduated optimization | is a | improvement to hill climbing that enables a hill climber to avoid settling into local optima | 0.90 | text |
| Graduated optimization | related to Related optimization techniques | Simulated | 0.60 | section |
| Graduated optimization | related to Related optimization techniques | Instead | 0.60 | section |
| Graduated optimization | related to Related optimization techniques | Because | 0.60 | section |
| Graduated optimization | related to Related optimization techniques | By | 0.60 | section |
| Graduated optimization | related to Some examples | Graduated | 0.60 | section |
| Graduated optimization | related to Some examples | This | 0.60 | section |
| Graduated optimization | related to Some examples | Thus | 0.60 | section |
| Graduated optimization | related to Some examples | The | 0.60 | section |
| Graduated optimization | related to Some examples | The Manifold Sculpting | 0.60 | section |
| Graduated optimization | related to Some examples | It | 0.60 | section |
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