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Convex function
In mathematics, a real-valued function defined on an n-dimensional interval is called convex (or convex downward or concave upward) if the line segment
Logarithmically convex function
In mathematics, a function f is logarithmically convex or superconvex if log ∘ f {\displaystyle {\log }\circ f} , the composition of the logarithm with
Proper convex function
mathematical analysis (in particular convex analysis) and optimization, a proper convex function is a convex function f taking values in the extended real
Convex optimization
Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets. Many classes of
Closed convex function
the function f ( x ) {\displaystyle f(x)} is closed. This definition is valid for any function, but most used for convex functions. A proper convex function
Convex set
the function) is a convex set. Convex minimization is a subfield of optimization that studies the problem of minimizing convex functions over convex sets
Concave function
function is the negative of a convex function. A concave function is also synonymously called concave downwards, concave down, convex upwards, convex
Schur-convex function
In mathematics, a Schur-convex function, also known as S-convex, isotonic function and order-preserving function is a function f : R d → R {\displaystyle
Piecewise linear function
piecewise linear functions and the convex piecewise linear functions. In general, for every n-dimensional continuous piecewise linear function f : R n → R
Convex conjugate
optimization, the convex conjugate of a function is a generalization of the Legendre transformation which applies to non-convex functions. It is also known