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  2. Extreme point - Wikipedia

    en.wikipedia.org/wiki/Extreme_point

    In mathematics, an extreme point of a convex set in a real or complex vector space is a point in that does not lie in any open line segment joining two points of . In linear programming problems, an extreme point is also called vertex or corner point of S . {\displaystyle S.} [ 1 ]

  3. Multivariable calculus - Wikipedia

    en.wikipedia.org/wiki/Multivariable_calculus

    Multivariable calculus (also known as multivariate calculus) is the extension of calculus in one variable to calculus with functions of several variables: the differentiation and integration of functions involving multiple variables (multivariate), rather than just one.

  4. Convex hull - Wikipedia

    en.wikipedia.org/wiki/Convex_hull

    For a convex hull, every extreme point must be part of the given set, because otherwise it cannot be formed as a convex combination of given points. According to the Krein–Milman theorem, every compact convex set in a Euclidean space (or more generally in a locally convex topological vector space) is the convex hull of its extreme points. [15]

  5. Calculus of variations - Wikipedia

    en.wikipedia.org/wiki/Calculus_of_Variations

    A simple example of such a problem is to find the curve of shortest length connecting two points. If there are no constraints, the solution is a straight line between the points. However, if the curve is constrained to lie on a surface in space, then the solution is less obvious, and possibly many solutions may exist.

  6. Function of several real variables - Wikipedia

    en.wikipedia.org/wiki/Function_of_several_real...

    The image of a function f(x 1, x 2, …, x n) is the set of all values of f when the n-tuple (x 1, x 2, …, x n) runs in the whole domain of f.For a continuous (see below for a definition) real-valued function which has a connected domain, the image is either an interval or a single value.

  7. Maximum and minimum - Wikipedia

    en.wikipedia.org/wiki/Maximum_and_minimum

    For example, x ∗ is a strict global maximum point if for all x in X with x ≠ x ∗, we have f(x ∗) > f(x), and x ∗ is a strict local maximum point if there exists some ε > 0 such that, for all x in X within distance ε of x ∗ with x ≠ x ∗, we have f(x ∗) > f(x). Note that a point is a strict global maximum point if and only if ...

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  9. Krein–Milman theorem - Wikipedia

    en.wikipedia.org/wiki/Krein–Milman_theorem

    Krein–Milman theorem [2] — Suppose is a Hausdorff locally convex topological vector space (for example, a normed space) and is a compact and convex subset of . Then is equal to the closed convex hull of its extreme points: = ¯ (⁡ ()).