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  2. Convex combination - Wikipedia

    en.wikipedia.org/wiki/Convex_combination

    A conical combination is a linear combination with nonnegative coefficients. When a point is to be used as the reference origin for defining displacement vectors, then is a convex combination of points ,, …, if and only if the zero displacement is a non-trivial conical combination of their respective displacement vectors relative to .

  3. Polyhedral combinatorics - Wikipedia

    en.wikipedia.org/wiki/Polyhedral_combinatorics

    Polyhedral combinatorics is a branch of mathematics, within combinatorics and discrete geometry, that studies the problems of counting and describing the faces of convex polyhedra and higher-dimensional convex polytopes. Research in polyhedral combinatorics falls into two distinct areas.

  4. Convex space - Wikipedia

    en.wikipedia.org/wiki/Convex_space

    In mathematics, a convex space (or barycentric algebra) is a space in which it is possible to take convex combinations of any sets of points. [ 1 ] [ 2 ] Formal Definition

  5. Frank–Wolfe algorithm - Wikipedia

    en.wikipedia.org/wiki/Frank–Wolfe_algorithm

    The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization.Also known as the conditional gradient method, [1] reduced gradient algorithm and the convex combination algorithm, the method was originally proposed by Marguerite Frank and Philip Wolfe in 1956. [2]

  6. Convex hull - Wikipedia

    en.wikipedia.org/wiki/Convex_hull

    In geometry, the convex hull, convex envelope or convex closure [1] of a shape is the smallest convex set that contains it. The convex hull may be defined either as the intersection of all convex sets containing a given subset of a Euclidean space, or equivalently as the set of all convex combinations of points in the subset.

  7. Convex optimization - Wikipedia

    en.wikipedia.org/wiki/Convex_optimization

    Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently, maximizing concave functions over convex sets). Many classes of convex optimization problems admit polynomial-time algorithms, [1] whereas mathematical optimization is in general NP-hard. [2 ...

  8. Convex function - Wikipedia

    en.wikipedia.org/wiki/Convex_function

    The term convex is often referred to as convex down or concave upward, and the term concave is often referred as concave down or convex upward. [ 3 ] [ 4 ] [ 5 ] If the term "convex" is used without an "up" or "down" keyword, then it refers strictly to a cup shaped graph ∪ {\displaystyle \cup } .

  9. List of convexity topics - Wikipedia

    en.wikipedia.org/wiki/List_of_convexity_topics

    Convex analysis - the branch of mathematics devoted to the study of properties of convex functions and convex sets, often with applications in convex minimization. Convex combination - a linear combination of points where all coefficients are non-negative and sum to 1. All convex combinations are within the convex hull of the given points.