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This paper introduces and studies the convergence properties of a new class of explicit $\epsilon$-subgradient methods for the task of minimizing a convex function over the set of minimizers of another convex minimization problem. The…

Optimization and Control · Mathematics 2019-04-03 Elias Salomão Helou , Lucas Eduardo Azevedo Simões

In this paper, we propose a new Fully Composite Formulation of convex optimization problems. It includes, as a particular case, the problems with functional constraints, max-type minimization problems, and problems of Composite…

Optimization and Control · Mathematics 2021-03-24 Nikita Doikov , Yurii Nesterov

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

We consider control-linear left-invariant time-optimal problems on step 2 Carnot groups with strictly convex set of control parameters (in particular, sub-Finsler problems). We describe all linear-in-momenta Casimirs on the dual of the Lie…

Optimization and Control · Mathematics 2020-03-18 Yuri L. Sachkov

We consider the nonconvex optimization problem associated with the decomposition of a real symmetric tensor into a sum of rank-one terms. Use is made of the rich symmetry structure to construct infinite families of critical points…

Optimization and Control · Mathematics 2025-08-07 Yossi Arjevani , Gal Vinograd

This study focuses on convex functions and their generalized. Thus, we start this study by giving the definition of convex functions and some of their properties and discussing a simple geometric property. Then we generalize E-convex…

Classical Analysis and ODEs · Mathematics 2017-04-27 Adem Kilicman , Wedad Saleh

Optimization problems with convex quadratic cost and polyhedral constraints are ubiquitous in signal processing, automatic control and decision-making. We consider here an enlarged problem class that allows to encode logical conditions and…

Optimization and Control · Mathematics 2026-04-09 Alberto De Marchi

We develop an algorithmic theory of convex optimization over discrete sets. Using a combination of algebraic and geometric tools we are able to provide polynomial time algorithms for solving broad classes of convex combinatorial…

Optimization and Control · Mathematics 2009-01-24 Shmuel Onn

Finslerian extensions of Special and General Relativity -- commonly referred to as Very Special and Very General Relativity -- necessitate the development of a unified Lorentz-Finsler geometry. However, the scope of this geometric framework…

General Relativity and Quantum Cosmology · Physics 2026-03-25 Miguel Sánchez

In this paper, is introduced a new proposal of resolvent for equilibrium problems in terms of the Busemann's function. A great advantage of this new proposal is that, in addition to be a natural extension of the proposal in the linear…

Optimization and Control · Mathematics 2021-11-09 G. C. Bento , J. X. Cruz Neto , I. D. L. Melo

We look for the minimizers of the functional $\jla{\la}(\oo)=\la|\oo|-P(\oo)$ among planar convex domains constrained to lie into a given ring. We prove that, according to the values of the parameter $\la$, the solutions are either a disc…

Analysis of PDEs · Mathematics 2010-12-22 Chiara Bianchini , Antoine Henrot

Generalized polyhedral convex sets, generalized polyhedral convex functions on locally convex Hausdorff topological vector spaces, and the related constructions such as sum of sets, sum of functions, directional derivative, infimal…

Optimization and Control · Mathematics 2017-05-22 Nguyen Ngoc Luan , Jen-Chih Yao , Nguyen Dong Yen

Many problems of theoretical and practical interest involve finding an optimum over a family of convex functions. For instance, finding the projection on the convex functions in $H^k(\Omega)$, and optimizing functionals arising from some…

Numerical Analysis · Mathematics 2008-04-11 Néstor E. Aguilera , Pedro Morin

Consider a convex function that is invariant under an group of transformations. If it has a minimizer, does it also have an invariant minimizer? Variants of this problem appear in nonparametric statistics and in a number of adjacent fields.…

Statistics Theory · Mathematics 2024-07-22 Peter Orbanz

As a natural application of the {\it theory of geometric averaging} in Finsler geometry and generalized Finsler geometry, a new approach to investigate {\it generalized Finsler geometry}, based on a convex invariance of the average…

Differential Geometry · Mathematics 2021-02-02 Ricardo Gallego Torromé

The book "Handbook of Finsler geometry" has been included with a CD containing an elegant Maple package, FINSLER, for calculations in Finsler geometry. Using this package, an example concerning a Finsler generalization of Einstein's vacuum…

Differential Geometry · Mathematics 2015-06-16 Nabil L. Youssef , S. G. Elgendi

We introduce a notion of $k$-convexity and explore polygons in the plane that have this property. Polygons which are \mbox{$k$-convex} can be triangulated with fast yet simple algorithms. However, recognizing them in general is a 3SUM-hard…

Computational Geometry · Computer Science 2010-07-22 Oswin Aichholzer , Franz Aurenhammer , Erik D. Demaine , Ferran Hurtado , Pedro Ramos , Jorge Urrutia

We describe a reformulation (following Hales (2017)) of a 1934 conjecture of Reinhardt on pessimal packings of convex domains in the plane as a problem in optimal control theory. Several structural results of this problem including its…

Optimization and Control · Mathematics 2022-08-10 Koundinya Vajjha

Let $\Omega\subset\mathbb{R}^{n+1}$ have minimal Gaussian surface area among all sets satisfying $\Omega=-\Omega$ with fixed Gaussian volume. Let $A=A_{x}$ be the second fundamental form of $\partial\Omega$ at $x$, i.e. $A$ is the matrix of…

Probability · Mathematics 2021-07-13 Steven Heilman

Hidden convexity is a powerful idea in optimization: under the right transformations, nonconvex problems that are seemingly intractable can be solved efficiently using convex optimization. We introduce the notion of a Lagrangian dual…

Optimization and Control · Mathematics 2025-11-07 Venkat Chandrasekaran , Timothy Duff , Jose Israel Rodriguez , Kevin Shu