Results 31 to 40 of about 482,837 (303)
In this paper, we give two weak conditions for a lower semi-continuous function on the n-dimensional Euclidean space Rn to be a convex function. We also present some results for convex functions, strictly convex functions, and quasi-convex functions.
Yu-Ru Syau
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Certain subclasses of uniformly convex functions of order α and type β with varying arguments
In this paper, we define a new subclass of k-uniformly convex functions order α type β with varying argument of coefficients and obtain coefficient estimates.
N. Magesh
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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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Inequalities of Hermite-Hadamard Type
Some inequalities of Hermite-Hadamard type for λ-convex functions defined on convex subsets in real or complex linear spaces are given. Applications for norm inequalities are provided as well.
Dragomir S. S.
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INEQUALITIES OF HERMITE-HADAMARD TYPE FOR HG-CONVEX FUNCTIONS
Some inequalities of Hermite-Hadamard type for HGconvex functions defined on positive intervals are given. Applications for special means are also provided.
S. S. Dragomir
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The paper provides the characteristic properties of half convex functions. The analytic and geometric image of half convex functions is presented using convex combinations and support lines. The results relating to convex combinations are applied to quasi-arithmetic means.
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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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Convex Multivariable Trace Functions
For any densely defined, lower semi-continuous trace \tau on a C*-algebra A with mutually commuting C*-subalgebras A_1, A_2, ... A_n, and a convex function f of n variables, we give a short proof of the fact that the function (x_1, x_2, ..., x_n ...
Lieb, Elliott H., Pedersen, Gert K.
core +1 more source
Conic geometric optimisation on the manifold of positive definite matrices
We develop \emph{geometric optimisation} on the manifold of Hermitian positive definite (HPD) matrices. In particular, we consider optimising two types of cost functions: (i) geodesically convex (g-convex); and (ii) log-nonexpansive (LN).
Hosseini, Reshad, Sra, Suvrit
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Precision‐Optimised Post‐Stroke Prognoses
ABSTRACT Background Current medicine cannot confidently predict who will recover from post‐stroke impairments. Researchers have sought to bridge this gap by treating the post‐stroke prognostic problem as a machine learning problem, reporting prediction error metrics across samples of patients whose outcomes are known.
Thomas M. H. Hope+4 more
wiley +1 more source