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It is established that general s-convex functions are a new class of generalized convex functions. In a similar vein, a new class of general s-convex sets is introduced, which are generalizations of s-convex sets. Additionally, certain…

Optimization and Control · Mathematics 2023-01-03 Musavvir Ali , Ehtesham Akhter

The notions of quasiconvexity, Wright convexity and convexity for functions defined on a metric Abelian group are introduced. Various characterizations of such functions, the structural properties of the functions classes so obtained are…

Classical Analysis and ODEs · Mathematics 2020-11-23 Włodzimierz Fechner , Zsolt Páles

In this paper, we establish the existence of the efficient solutions for polynomial vector optimization problems on a nonempty closed constraint set without any convexity and compactness assumptions. We first introduce the relative…

Optimization and Control · Mathematics 2025-08-08 Danyang Liu

Functions with uniform level sets can represent orders, preference relations or other binary relations and thus turn out to be a tool for scalarization that can be used, e.g., in multicriteria optimization, decision theory, mathematical…

Optimization and Control · Mathematics 2016-08-11 Petra Weidner

We study the usage of regularity properties of collections of sets in convergence analysis of alternating projection methods for solving feasibility problems. Several equivalent characterizations of these properties are provided. Two…

Optimization and Control · Mathematics 2018-02-27 Alexander Y. Kruger , Nguyen H. Thao

We consider projection algorithms for solving (nonconvex) feasibility problems in Euclidean spaces. Of special interest are the Method of Alternating Projections (MAP) and the Douglas-Rachford or Averaged Alternating Reflection Algorithm…

Optimization and Control · Mathematics 2014-03-17 Robert Hesse , D. Russell Luke

In this work, we introduce a new class of non-convex functions, called implicit concave functions, which are compositions of a concave function with a continuously differentiable mapping. We analyze the properties of their minimization by…

Optimization and Control · Mathematics 2025-10-08 Vittorio Latorre

A key idea in convex optimization theory is to use well-structured affine functions to approximate general functions, leading to impactful developments in conjugate functions and convex duality theory. This raises the question: what are the…

Optimization and Control · Mathematics 2025-04-22 Ningji Wei

We establish existence results for a class of mixed anisotropic and nonlocal $p$-Laplace equation with singular nonlinearities. We consider both constant and variable singular exponents. Our argument is based on an approximation method. To…

Analysis of PDEs · Mathematics 2023-03-28 Prashanta Garain , Wontae Kim , Juha Kinnunen

We introduce a new notion of "regularity structure" that provides an algebraic framework allowing to describe functions and / or distributions via a kind of "jet" or local Taylor expansion around each point. The main novel idea is to…

Analysis of PDEs · Mathematics 2015-06-15 Martin Hairer

Expectiles were introduced by Newey and Powell (1987) in the context of linear regression models. Recently, Bellini et al. (2014) revealed that expectiles can also be seen as reasonable law-invariant risk measures. In this article, we show…

Statistics Theory · Mathematics 2016-09-21 Volker Krätschmer , Henryk Zähle

One of the key assumptions in the stability and convergence analysis of variational regularization is the ability of finding global minimizers. However, such an assumption is often not feasible when the regularizer is a black box or…

Optimization and Control · Mathematics 2023-07-05 Daniel Obmann , Markus Haltmeier

We study the smooth structure of convex functions by generalizing a powerful concept so-called self-concordance introduced by Nesterov and Nemirovskii in the early 1990s to a broader class of convex functions, which we call generalized…

Optimization and Control · Mathematics 2018-05-09 Tianxiao Sun , Quoc Tran-Dinh

We consider the problem of convergence to a saddle point of a concave-convex function via gradient dynamics. Since first introduced by Arrow, Hurwicz and Uzawa in [1] such dynamics have been extensively used in diverse areas, there are,…

Optimization and Control · Mathematics 2019-08-06 Thomas Holding , Ioannis Lestas

Nonconvex regularization has been popularly used in low-rank matrix learning. However, extending it for low-rank tensor learning is still computationally expensive. To address this problem, we develop an efficient solver for use with a…

Machine Learning · Computer Science 2022-05-09 Quanming Yao , Yaqing Wang , Bo Han , James Kwok

Overlap functions were introduced as class of bivariate aggregation functions on [0, 1] to be applied in image processing. This paper has as main objective to present appropriates definitions of overlap functions considering the scope of…

Logic in Computer Science · Computer Science 2019-02-04 Rui Paiva , Eduardo Palmeira , Regivan Santiago , Benjamin Bedregal

The first two authors of this paper asserted in Lemma 4 of "New Farkas-type constraint qualifications in convex infinite programming" (DOI: 10.1051/cocv:2007027) that a given reverse convex inequality is consequence of a given convex system…

Optimization and Control · Mathematics 2023-05-31 Nguyen Dinh , Miguel A. Goberna , M. Volle

Uniformly regular equilibrium problems are natural generalizations of abstract equilibrium prob lems and they are defined over the uniformly prox-regular nonconvex sets. Some new efficient implicit methods for solving uniformly regular…

Optimization and Control · Mathematics 2025-02-11 Oday Hazaimah

We present here a new method for approximating functions defined on superreflexive Banach spaces by differentiable functions with $\alpha$-H\"older derivatives (for some $0<\alpha\leq 1$). The smooth approximation is given by means of an…

Functional Analysis · Mathematics 2016-09-07 Manuel Cepedello Boiso

The subject of this paper is regularity-preserving aggregation of regular norms on finite-dimensional linear spaces. Regular norms were introduced in [5] and are closely related to ``type 2'' spaces [9, Chapter 9] playing important role in…

Optimization and Control · Mathematics 2024-02-13 Anatoli Juditsky , Arkadi Nemirovski