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  2. Convex optimization - Wikipedia

    en.wikipedia.org/wiki/Convex_optimization

    In the standard form it is possible to assume, without loss of generality, that the objective function f is a linear function.This is because any program with a general objective can be transformed into a program with a linear objective by adding a single variable t and a single constraint, as follows: [9]: 1.4

  3. Concave function - Wikipedia

    en.wikipedia.org/wiki/Concave_function

    A function f is concave over a convex set if and only if the function −f is a convex function over the set. The sum of two concave functions is itself concave and so is the pointwise minimum of two concave functions, i.e. the set of concave functions on a given domain form a semifield.

  4. Convex function - Wikipedia

    en.wikipedia.org/wiki/Convex_function

    In simple terms, a convex function graph is shaped like a cup (or a straight line like a linear function), while a concave function's graph is shaped like a cap . A twice-differentiable function of a single variable is convex if and only if its second derivative is nonnegative on its entire domain. [1]

  5. Logarithmically concave function - Wikipedia

    en.wikipedia.org/wiki/Logarithmically_concave...

    This follows from the fact that the convolution of two log-concave functions is log-concave. The product of two log-concave functions is log-concave. This means that joint densities formed by multiplying two probability densities (e.g. the normal-gamma distribution, which always has a shape parameter ≥ 1) will be log-concave.

  6. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    Otherwise, if a feasible solution exists and if the constraint set is bounded, then the optimum value is always attained on the boundary of the constraint set, by the maximum principle for convex functions (alternatively, by the minimum principle for concave functions) since linear functions are both convex and concave. However, some problems ...

  7. Category:Types of functions - Wikipedia

    en.wikipedia.org/wiki/Category:Types_of_functions

    Periodic function; List of periodic functions; Pfaffian function; Piecewise linear function; Piecewise property; Polyconvex function; Positive-definite function; Positive-real function; Progressive function; Proper convex function; Proto-value function; Pseudoanalytic function; Pseudoconvex function

  8. List of types of functions - Wikipedia

    en.wikipedia.org/wiki/List_of_types_of_functions

    p-adic function: a function whose domain is p-adic. Linear function; also affine function. Convex function: line segment between any two points on the graph lies above the graph. Also concave function. Arithmetic function: A function from the positive integers into the complex numbers. Analytic function: Can be defined locally by a convergent ...

  9. Convex conjugate - Wikipedia

    en.wikipedia.org/wiki/Convex_conjugate

    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).