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A formula for the sub\-differential of the sum of a series of convex functions defined on a Banach space was provided by X. Y. Zheng in 1998. In this paper, besides a slight extension to locally convex spaces of Zheng's results, we provide…

Optimization and Control · Mathematics 2015-06-04 C. Vallee , C. Zalinescu

In this note we explore duality in reverse convex optimization with reverse convex inequality constraints. While we are examining the special case of a finite index set of the inequality constraints, we are primarily interested in the…

Optimization and Control · Mathematics 2023-08-07 Joachim Gwinner

We obtain operator concavity (convexity) of some functions of two or three variables by using perspectives of regular operator mappings of one or several variables. As an application, we obtain, for $ 0<p < 1,$ concavity, respectively…

Functional Analysis · Mathematics 2014-06-09 Zhihua Zhang

We associate with each convex optimization problem, posed on some locally convex space, with infinitely many constraints indexed by the set T, and a given non-empty family H of finite subsets of T, a suitable Lagrangian-Haar dual problem.…

Optimization and Control · Mathematics 2021-06-04 Nguyen Dih , Miguel A. Goberna , Marco A. López , Michel Volle

We investigate regularity properties of generalized conjugate functions induced by a general coupling function and the associated generalized proximal mapping. Our main results provide verifiable conditions ensuring local single-valuedness,…

Optimization and Control · Mathematics 2026-04-07 Konstantinos Oikonomidis , Emanuel Laude , Panagiotis Patrinos

We study the mixed-integer epigraph of a special class of convex functions with non-convex indicator constraints, which are often used to impose logical constraints on the support of the solutions. The class of functions we consider are…

Optimization and Control · Mathematics 2023-09-19 Shaoning Han , Andrés Gómez

One revisits the standard saddle-point method based on conjugate duality for solving convex minimization problems. Our aim is to reduce or remove unnecessary topological restrictions on the constraint set. Dual equalities and…

Optimization and Control · Mathematics 2007-10-09 Christian Léonard

We continue the analysis in [3] of matrix convex functions of a fixed order defined in a real interval by differential methods as opposed to the characterization in terms of divided differences given by Kraus [5]. We amend and improve some…

Operator Algebras · Mathematics 2007-05-23 Frank Hansen , Jun Tomiyama

Recently, Yamanaka and Yamashita proposed the so-called positively homogeneous optimization problem, which includes many important problems, such as the absolute-value and the gauge optimizations. They presented a closed form of the dual…

Optimization and Control · Mathematics 2020-12-29 Shota Yamanaka , Nobuo Yamashita

We consider minimization of functions that are compositions of convex or prox-regular functions (possibly extended-valued) with smooth vector functions. A wide variety of important optimization problems fall into this framework. We describe…

Optimization and Control · Mathematics 2015-04-24 A. S. Lewis , S. J. Wright

This paper explores a method for solving constrained optimization problems when the derivatives of the objective function are unavailable, while the derivatives of the constraints are known. We allow the objective and constraint function to…

Optimization and Control · Mathematics 2024-02-20 Melody Qiming Xuan , Jorge Nocedal

We provide sharp and explicit characterizations of the normal cone to sublevel sets of suprema of arbitrary functions, expressed exclusively in terms of subdifferentials of the data functions. In the convex case, the resulting formulas…

Optimization and Control · Mathematics 2026-02-12 Stephanie Caro , Rafael Correa , Abderrahim Hantoute

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

We consider minimization of stochastic functionals that are compositions of a (potentially) non-smooth convex function $h$ and smooth function $c$ and, more generally, stochastic weakly-convex functionals. We develop a family of stochastic…

Optimization and Control · Mathematics 2018-09-25 John Duchi , Feng Ruan

This paper provides versions of classical results from linear algebra, real analysis and convex analysis in a free module of finite rank over the ring $L^0$ of measurable functions on a $\sigma$-finite measure space. We study the question…

Functional Analysis · Mathematics 2014-10-27 Patrick Cheridito , Michael Kupper , Nicolas Vogelpoth

We introduce and investigate a new generalized convexity notion for functions called prox-convexity. The proximity operator of such a function is single-valued and firmly nonexpansive. We provide examples of (strongly) quasiconvex, weakly…

Optimization and Control · Mathematics 2021-11-30 Sorin-Mihai Grad , Felipe Lara

In this paper we consider a composite optimization problem that minimizes the sum of a weakly smooth function and a convex function with either a bounded domain or a uniformly convex structure. In particular, we first present a…

Optimization and Control · Mathematics 2023-05-30 Masaru Ito , Zhaosong Lu , Chuan He

This paper explores local second-order weak sharp minima for a broad class of nonconvex optimization problems. We propose novel second-order optimality conditions formulated through the use of classical and lower generalized support…

Optimization and Control · Mathematics 2025-07-18 Xiaoxiao Ma , Wei Ouyang , Jane Ye , Binbin Zhang

The goal of the paper is to study the particular class of regularly ${\mathcal{H}}$-convex functions, when ${\mathcal{H}}$ is the set ${\mathcal{L}\widehat{C}}(X,{\mathbb{R}})$ of real-valued Lipschitz continuous classically concave…

Optimization and Control · Mathematics 2022-08-03 Valentin V. Gorokhovik

We consider the problem of chasing convex functions, where functions arrive over time. The player takes actions after seeing the function, and the goal is to achieve a small function cost for these actions, as well as a small cost for…

Data Structures and Algorithms · Computer Science 2020-05-29 C. J. Argue , Anupam Gupta , Guru Guruganesh