Danskin's theorem, in convex analysis, gives a formula for the derivative of a function defined as the pointwise maximum over a family of functions. It has applications in optimization, including the solution of minimax problems; J. M. Danskin proved the original version in a 1967 monograph, giving a formula for the directional derivative of the maximum of a directionally differentiable function that need not be convex, and Dimitri Bertsekas proved an extension to more general conditions in 1971. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/
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In convex analysis, Danskin's theorem is a theorem which provides information about the derivatives of a function of the form f ( x ) = max z ∈ Z ϕ ( x , z ) . {\displaystyle f(x)=\max _{z\in Z}\phi (x,z).} The theorem has applications in optimization, where it sometimes is used to solve minimax problems.
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In convex analysis, Danskin's theorem is a theorem which provides information about the derivatives of a function
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