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In mathematics, the subderivative (or subgradient) generalizes the derivative to convex functions which are not necessarily differentiable. The set of subderivatives at a point is called the subdifferential at that point. Subderivatives arise in convex analysis, the study of convex functions, often in connection to convex optimization.
History, The subgradient & Definition
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| Subject | Predicate | Object | Confidence | Src |
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| Subderivative | related to Definition | Rigorously | 0.60 | section |
| Subderivative | related to Definition | By | 0.60 | section |
| Subderivative | related to Definition | The | 0.60 | section |
| Subderivative | related to Definition | If | 0.60 | section |
| Subderivative | related to Definition | Moreover | 0.60 | section |
| Subderivative | related to Examples | Consider | 0.60 | section |
| Subderivative | related to Examples | Then | 0.60 | section |
| Subderivative | related to Examples | The | 0.60 | section |
| Subderivative | related to Examples | This | 0.60 | section |
| Subderivative | related to Examples | More | 0.60 | section |
| Subderivative | related to The subgradient | The | 0.60 | section |
| Subderivative | related to The subgradient | If | 0.60 | section |
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