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Strongly Convex Functions of Higher Order Involving Bifunction
Some new concepts of the higher order strongly convex functions involving an arbitrary bifuction are considered in this paper. Some properties of the higher order strongly convex functions are investigated under suitable conditions.
Bandar B. Mohsen+3 more
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Functions Like Convex Functions [PDF]
The paper deals with convex sets, functions satisfying the global convexity property, and positive linear functionals. Jensen's type inequalities can be obtained by using convex combinations with the common center. Following the idea of the common center, the functional forms of Jensen's inequality are considered in this paper.
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Convex relaxations of componentwise convex functions
Published by Elsevier Science, Amsterdam [u.a.]
Najman, Jaromil+2 more
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It is shown that inversion is a convex function on the set of strictly positive elements of a C*-algebra.
Derming Wang
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The Ostrowski inequality for s-convex functions in the third sense
In this paper, the Ostrowski inequality for s-convex functions in the third sense is studied. By applying Hölder and power mean integral inequalities, the Ostrowski inequality is obtained for the functions, the absolute values of the powers of whose ...
Gültekin Tınaztepe +3 more
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Quotients of continuous convex functions on nonreflexive Banach spaces [PDF]
On each nonreflexive Banach space X there exists a positive continuous convex function f such that 1/f is not a d.c. function (i.e., a difference of two continuous convex functions). This result together with known ones implies that X is reflexive if and
Holicky, P.+3 more
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Inclusion and Intersection Relations Between Fundamental Classes of Discrete Convex Functions [PDF]
In discrete convex analysis, various convexity concepts are considered for discrete functions such as separable convexity, L-convexity, M-convexity, integral convexity, and multimodularity. These concepts of discrete convex functions are not mutually independent.
arxiv
Projections Onto Convex Sets (POCS) Based Optimization by Lifting [PDF]
Two new optimization techniques based on projections onto convex space (POCS) framework for solving convex and some non-convex optimization problems are presented.
Bozkurt, A.+7 more
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Modulus of convexity for operator convex functions [PDF]
Given an operator convex function f(x), we obtain an operator-valued lower bound for cf(x) + (1 − c)f(y) − f(cx + (1 − c)y), c ∈ [0, 1]. The lower bound is expressed in terms of the matrix Bregman divergence. A similar inequality is shown to be false for functions that are convex but not operator convex.
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On uniformly convex functions [PDF]
Non-convex functions that yet satisfy a condition of uniform convexity for non-close points can arise in discrete constructions. We prove that this sort of discrete uniform convexity is inherited by the convex envelope, which is the key to obtain other remarkable properties such as the coercivity.
M. Raja, Guillaume Grelier
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