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In this article, we further explore convex functions by revealing new bounds, resulting from stronger convexity behavior. In particular, we define the so called radical convex functions and study their properties. We will see that such…

Functional Analysis · Mathematics 2020-10-13 Mohammad Sababheh , Hamid Reza Moradi

We consider composite loss functions for multiclass prediction comprising a proper (i.e., Fisher-consistent) loss over probability distributions and an inverse link function. We establish conditions for their (strong) convexity and explore…

Machine Learning · Computer Science 2012-06-22 Mark Reid , Robert Williamson , Peng Sun

Submodular functions are relevant to machine learning for at least two reasons: (1) some problems may be expressed directly as the optimization of submodular functions and (2) the lovasz extension of submodular functions provides a useful…

Machine Learning · Computer Science 2013-10-09 Francis Bach

Submodularity is an important concept in combinatorial optimization, and it is often regarded as a discrete analog of convexity. It is a fundamental fact that the set of minimizers of any submodular function forms a distributive lattice.…

Discrete Mathematics · Computer Science 2019-10-14 Tomohito Fujii , Shuji Kijima

In this study, we obtain some new integral inequalities for different classes of convex functions by using some elementary inequalities and classical inequalities like general Cauchy inequality and Minkowski inequality.

Classical Analysis and ODEs · Mathematics 2012-02-10 M. Emin Ozdemir , Alper Ekinci , Ahmet Ocak Akdemir

We consider mesh functions which are discrete convex in the sense that their central second order directional derivatives are positive. Analogous to the case of a uniformly bounded sequence of convex functions, we prove that the uniform…

Numerical Analysis · Mathematics 2019-11-01 Gerard Awanou

A jump system is defined as a set of integer points (vectors) with a certain exchange property, generalizing the concepts of matroids, delta-matroids, and base polyhedra of integral polymatroids (or submodular systems). A discrete convexity…

Combinatorics · Mathematics 2020-09-21 Kazuo Murota

This paper studies system theoretic properties of the class of difference inclusions of convex processes. We will develop a framework considering eigenvalues and eigenvectors, weakly and strongly invariant cones, and a decomposition of…

Optimization and Control · Mathematics 2021-12-30 Jaap Eising , M. Kanat Camlibel

We investigate an enriched-categorical approach to a field of discrete mathematics. The main result is a duality theorem between a class of enriched categories (called $\overline{\mathbb{Z}}$- or $\overline{\mathbb{R}}$-categories) and that…

Category Theory · Mathematics 2019-04-19 Soichiro Fujii

In this paper we show how the superquadratic functions can be used as a tool for researching other types of convex functions like $\phi $-convexity, strong-convexity and uniform convexity. We show how to use inequalities satisfied by…

Functional Analysis · Mathematics 2024-08-15 Shoshana Abramovich

We treat the classical notion of convexity in the context of hard real analysis. Definitions of the concept are given in terms of defining functions and quadratic forms, and characterizations are provided of different concrete notions of…

Classical Analysis and ODEs · Mathematics 2009-09-01 Steven G. Krantz

A class of real functions, which is the generalization of a family of convex functions, is introduced; in this connection, we have defined $X$-convex, strictly $X$-convex, quasi-$X$-convex, strictly quasi-$X$-convex, and semi-strictly…

Optimization and Control · Mathematics 2022-08-16 Musavvir Ali , Ehtesham Akhter

Submodular set-functions have many applications in combinatorial optimization, as they can be minimized and approximately maximized in polynomial time. A key element in many of the algorithms and analyses is the possibility of extending the…

Machine Learning · Computer Science 2016-02-24 Francis Bach

In many naturally occurring optimization problems one needs to ensure that the definition of the optimization problem lends itself to solutions that are tractable to compute. In cases where exact solutions cannot be computed tractably, it…

Machine Learning · Computer Science 2015-05-08 Bharath Sankaran , Marjan Ghazvininejad , Xinran He , David Kale , Liron Cohen

This article characterizes conjugates and subdifferentials of convex integral functionals over linear spaces of cadlag stochastic processes. The approach is based on new measurability results on the Skorokhod space and new interchange rules…

Optimization and Control · Mathematics 2018-12-12 Ari-Pekka Perkkiö , Erick Treviño-Aguilar

In this paper, a new class of convex functions as a generalization of convexity which is called (h-m)-convex functions and some properties of this class is given. We also prove some Hadamard's type inequalities.

Classical Analysis and ODEs · Mathematics 2011-04-01 M. E. Ozdemir , Ahmet Ocak Akdemir , Erhan Set

Submodular functions are discrete functions that model laws of diminishing returns and enjoy numerous algorithmic applications. They have been used in many areas, including combinatorial optimization, machine learning, and economics. In…

Data Structures and Algorithms · Computer Science 2012-08-24 Maria-Florina Balcan , Nicholas J. A. Harvey

In this paper we established new integral inequalities which are more general results for coordinated convex functions on the coordinates by using some classical inequalities.

Classical Analysis and ODEs · Mathematics 2011-07-21 M. Emin Ozdemir , Cetin Yildiz , Ahmet Ocak Akdemir

In this paper, approximate convexity and approximate midconvexity properties, called $\varphi$-convexity and $\varphi$-midconvexity, of real valued function are investigated. Various characterizations of $\varphi$-convex and…

Classical Analysis and ODEs · Mathematics 2012-11-21 Judit Makó , Zsolt Páles

During the study of the topic of limit summability of functions (introduced by the author in 2001), we encountered some types of functions that are related to the mean value theorem. In this paper, we formally define mean value and…

Classical Analysis and ODEs · Mathematics 2021-10-01 M. H. Hooshmand