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In mathematics and mathematical optimization, the convex conjugate of a function is a generalization of the Legendre transformation which applies to non-convex functions. It is also known as Legendre–Fenchel transformation, Fenchel transformation, or Fenchel conjugate (after Adrien-Marie Legendre and Werner Fenchel). The convex conjugate is widely used…
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Convex conjugate | is a | function f | 0.90 | text |
| Convex conjugate | related to Biconjugate | The | 0.60 | section |
| Convex conjugate | related to Biconjugate | For | 0.60 | section |
| Convex conjugate | related to Biconjugate | The Fenchel | 0.60 | section |
| Convex conjugate | related to Biconjugate | More | 0.60 | section |
| Convex conjugate | related to Biconjugate | In | 0.60 | section |
| Convex conjugate | related to Biconjugate | Fenchel | 0.60 | section |
| Convex conjugate | related to Biconjugate | Moreau | 0.60 | section |
| Convex conjugate | related to Connection with expected shortfall (average value at risk) | See | 0.60 | section |
| Convex conjugate | related to Connection with expected shortfall (average value at risk) | Let | 0.60 | section |
| Convex conjugate | related to Connection with expected shortfall (average value at risk) | Then | 0.60 | section |
| Convex conjugate | related to Examples | For | 0.60 | section |
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