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Related papers: Quasi-Herglotz functions and convex optimization

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Let $\Delta_m$ be the standard $m$-dimensional simplex of non-negative $m+1$ tuples that sum to unity and let $S$ be a nonempty subset of $\Delta_m$. A real valued function $h$ defined on a convex subset of a real vector space is $S$-almost…

Functional Analysis · Mathematics 2007-05-23 S. J. Dilworth , Ralph Howard , James W. Roberts

This paper focuses on investigating generalized relative interior notions for sets in locally convex topological vector spaces with particular attentions to graphs of set-valued mappings and epigraphs of extended-real-valued functions. We…

Optimization and Control · Mathematics 2023-08-01 Vo Si Trong Long , Boris Mordukhovich , Nguyen Mau Nam

We apply upper and lower compensated convex transforms, which are `tight' one-sided approximations of a given function, to the extraction of fine geometric singularities from semiconvex/semiconcave functions and DC-functions in…

Optimization and Control · Mathematics 2016-10-06 Kewei Zhang , Elaine Crooks , Antonio Orlando

We introduce the notions of pointwise almost h-slant submanifolds and pointwise almost h-semi-slant submanifolds as a generalization of slant submanifolds, pointwise slant submanifolds, semi-slant submanifolds, and pointwise semi-slant…

Differential Geometry · Mathematics 2016-01-14 Kwang-Soon Park

In classical inverse linear optimization, one assumes a given solution is a candidate to be optimal. Real data is imperfect and noisy, so there is no guarantee this assumption is satisfied. Inspired by regression, this paper presents a…

Optimization and Control · Mathematics 2017-06-23 Timothy C. Y. Chan , Taewoo Lee , Daria Terekhov

We introduce the multiple zeta functions with structures similar to those of symmetric functions such as Schur $P$-, Schur $Q$-, symplectic and orthogonal functions in the representation theory. We first consider their basic properties such…

Number Theory · Mathematics 2022-08-26 Maki Nakasuji , Wataru Takeda

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

In this paper, we consider stochastic second-order methods for minimizing a finite summation of nonconvex functions. One important key is to find an ingenious but cheap scheme to incorporate local curvature information. Since the true…

Optimization and Control · Mathematics 2021-03-26 Minghan Yang , Dong Xu , Hongyu Chen , Zaiwen Wen , Mengyun Chen

This note deals with certain properties of convex functions. We provide results on the convexity of the set of minima of these functions, the behaviour of their subgradient set under restriction, and optimization of these functions over an…

Optimization and Control · Mathematics 2017-03-21 Miel Sharf , Daniel Zelazo

Optimizing an implicational base of a closure system consists in turning this implicational base into an equivalent one with premises and conclusions as small as possible. This task is known to be hard in general but tractable for a number…

Combinatorics · Mathematics 2026-03-17 Anthony Meunier , Lhouari Nourine , Simon Vilmin

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

We introduced the quasicentral modulus to study normed ideal perturbations of operators. It is a limit of condenser quasicentral moduli in view of a recently noticed analogy with capacity in nonlinear potential theory. We prove here some…

Functional Analysis · Mathematics 2022-08-16 Dan-Virgil Voiculescu

We characterize when the level sets of a continuous quasi-monotone functional defined on a suitable convex subset of a normed space can be uniquely represented by a family of bounded continuous functionals. Furthermore, we investigate how…

Optimization and Control · Mathematics 2015-08-24 Ingo Steinwart

We study the fundamental properties of pointwise semi-Lipschitz functions between asymmetric spaces, which are the natural asymmetric counterpart of pointwise Lipschitz functions. We also study the influence that partial symmetries of a…

Functional Analysis · Mathematics 2024-10-10 Estíbalitz Durand-Cartagena , Jesús Á. Jaramillo , Francisco Venegas M

This paper is concerned with applications of the theory of approximation and interpolation based on compensated convex transforms developed in [K. Zhang, E. Crooks, A. Orlando, Compensated convexity methods for approximations and…

Metric Geometry · Mathematics 2018-09-11 Kewei Zhang , Elaine Crooks , Antonio Orlando

This paper presents a tractable algorithm for estimating an unknown Lipschitz function from noisy observations and establishes an upper bound on its convergence rate. The approach extends max-affine methods from convex shape-restricted…

Machine Learning · Statistics 2025-11-20 Gábor Balázs

A production function $f$ is called quasi-sum if there are strict monotone functions $F, h_1,...,h_n$ with $F'>0$ such that $$f(x)= F(h_1 (x_1)+...+h_n (x_n)).$$ The justification for studying quasi-sum production functions is that these…

Optimization and Control · Mathematics 2013-07-16 Bang-Yen Chen

Similar to linear spaces, many examples of quasilinear spaces have a notion of multiplication of the elements. To characterising these examples, in the present paper we generalize the notion of quasilinear spaces and introduce…

Functional Analysis · Mathematics 2020-10-20 Reza Dehghanizade , Seyed Mohamad Sadegh Modarres Mosadegh

We consider a class of nonconvex energy functionals that lies in the framework of the peridynamics model of continuum mechanics. The energy densities are functions of a nonlocal strain that describes deformation based on pairwise…

Analysis of PDEs · Mathematics 2023-06-28 Tadele Mengesha , James M. Scott

Optimization of convex functions subject to eigenvalue constraints is intriguing because of peculiar analytical properties of eigenvalues, and is of practical interest because of wide range of applications in fields such as structural…

Numerical Analysis · Mathematics 2013-10-08 Emre Mengi