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Extending classical results on polytopal approximation of convex bodies, we derive asymptotic formulas for the weighted approximation of smooth convex functions by piecewise affine convex functions as the number of their facets tends to…

Optimization and Control · Mathematics 2025-10-01 Fernanda M. Baêta

Optimization problems with composite functions consist of an objective function which is the sum of a smooth and a (convex) nonsmooth term. This particular structure is exploited by the class of proximal gradient methods and some of their…

Optimization and Control · Mathematics 2022-10-17 Christian Kanzow , Theresa Lechner

We consider families of quasisymmetric functions with the property that if a symmetric function $f$ is a positive sum of functions in one of these families, then f is necessarily a positive sum of Schur functions. Furthermore, in each of…

Combinatorics · Mathematics 2015-08-31 Austin Roberts

Let $E$ be a real vector space with dual space $E^*$ and let $C\subset E$ be a convex subset with more than one point. Let $f : C\to\mathbb{R}$ be a function satisfying a mild stability property at 'flat' points of the (relative) boundary…

Optimization and Control · Mathematics 2015-04-21 Khanh Pham Duy , Marc Lassonde

Euclidean functions with values in an arbitrary well-ordered set were first considered in a 1949 work of Motzkin and studied in more detail in work of Fletcher, Samuel and Nagata in the 1970's and 1980's. Here these results are revisited,…

Commutative Algebra · Mathematics 2012-08-07 Pete L. Clark

In a very influential paper Gehring and Palka introduced the notions of quasiconformally homogeneous and uniformly quasiconformally homogeneous subsets of Euclidean space. Their motivation was to provide a characterization of quasi-disks,…

Complex Variables · Mathematics 2014-01-16 Petra Bonfert-Taylor , Richard Canary , Edward Taylor

Mixed volumes, which are the polarization of volume with respect to the Minkowski addition, are fundamental objects in convexity. In this note we announce the construction of mixed integrals, which are functional analogs of mixed volumes.…

Functional Analysis · Mathematics 2013-02-05 Vitali Milman , Liran Rotem

In this paper, we introduce the concept of nearly convex set-valued mappings and investigate fundamental properties of these mappings. Additionally, we establish a geometric approach for generalized differentiation of nearly convex…

Optimization and Control · Mathematics 2023-02-20 Nguyen Mau Nam , Nguyen Nang Thieu , Nguyen Dong Yen

In this paper we associate with an infinite family of real extended functions defined on a locally convex space, a sum, called robust sum, which is always well-defined. We also associate with that family of functions a dual pair of problems…

Optimization and Control · Mathematics 2018-11-07 Nguyen Dinh , Miguel A. Goberna , Michel Volle

Minimization is a reoccurring theme in many mathematical disciplines ranging from pure to applied ones. Of particular importance is the minimization of integral functionals that is studied within the calculus of variations. Proofs of the…

Analysis of PDEs · Mathematics 2017-11-09 Barbora Benešová , Martin Kružík

We extend the standard notion of self-concordance to non-convex optimization and develop a family of second-order algorithms with global convergence guarantees. In particular, two function classes -- \textit{weakly self-concordant}…

Optimization and Control · Mathematics 2026-04-07 Donald Goldfarb , Lexiao Lai , Tianyi Lin , Jiayu Zhang

A new class of convex functions called functions, Young functions, strong Young functions and Orlicz functions are introduced by relaxing the definitions of functions, Young functions, strong Young functions and Orlicz functions. Then, new…

Functional Analysis · Mathematics 2019-05-16 Abdulhameed Qahtan Abbood Altai , Nada Mohammed Abbas Alsafar

In this paper, we introduce new properties of the relative interior calculus for nearly convex sets, functions, and set-valued mappings. These properties are important for the development of duality theory in optimization. Then we…

Optimization and Control · Mathematics 2023-03-15 Nguyen Quang Huy , Nguyen Mau Nam , Nguyen Dong Yen

We consider the space of convex functions defined in the Euclidean $n$-dimensional space, which are lower semi-continuous and tend to infinity at infinity. We study real-valued valuations defined on this space of functions, which are…

Metric Geometry · Mathematics 2015-08-04 L. Cavallina , A. Colesanti

In this paper we present a new kind of semigroups called convex body semigroups which are generated by convex bodies of R^k. They generalize to arbitrary dimension the concept of proportionally modular numerical semigroup of [7]. Several…

Commutative Algebra · Mathematics 2013-10-15 J. I. García-García , M. A. Moreno-Frías , A. Sánchez-R. -Navarro , A. Vigneron-Tenorio

A survey of properties of the adjunction involving a semisymmetrization functor, which was suggested by J.D.H. Smith, and which maps the category of quasigroups with homotopies to the category of semisymmetric quasigroups with…

Category Theory · Mathematics 2016-01-13 Aleksandar Krapez , Zoran Petric

In this paper, we prove some new inequalities of Simpson's type for functions whose derivatives of absolute values are h-convex and h-concave functions. Some new estimations are obtained. Also we give some sophisticated results for some…

Classical Analysis and ODEs · Mathematics 2014-02-03 Mevlut Tunc , Cetin Yildiz , Alper Ekinci

A closed quasigeodesic is a closed curve on the surface of a polyhedron with at most $180^\circ$ of surface on both sides at all points; such curves can be locally unfolded straight. In 1949, Pogorelov proved that every convex polyhedron…

Computational Geometry · Computer Science 2025-10-21 Erik D. Demaine , Adam C. Hesterberg , Jason S. Ku

In this article we utilise abstract convexity theory in order to unify and generalize many different concepts from nonsmooth analysis. We introduce the concepts of abstract codifferentiability, abstract quasidifferentiability and abstract…

Optimization and Control · Mathematics 2018-10-03 M. V. Dolgopolik

The Heavy Ball Method, proposed by Polyak over five decades ago, is a first-order method for optimizing continuous functions. While its stochastic counterpart has proven extremely popular in training deep networks, there are almost no known…

Machine Learning · Computer Science 2021-02-16 Jun-Kun Wang , Jacob Abernethy
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