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We prove bounds for the covering numbers of classes of convex functions and convex sets in Euclidean space. Previous results require the underlying convex functions or sets to be uniformly bounded. We relax this assumption and replace it…

Information Theory · Computer Science 2014-10-24 Adityanand Guntuboyina

Submodular continuous functions are a category of (generally) non-convex/non-concave functions with a wide spectrum of applications. We characterize these functions and demonstrate that they can be maximized efficiently with approximation…

Machine Learning · Computer Science 2019-05-07 Andrew An Bian , Baharan Mirzasoleiman , Joachim M. Buhmann , Andreas Krause

Optimization problems with uncertainty in the constraints occur in many applications. Particularly, probability functions present a natural form to deal with this situation. Nevertheless, in some cases, the resulting probability functions…

Optimization and Control · Mathematics 2023-01-25 Wim van Ackooij , Pedro Pérez-Aros , Claudia Soto , Emilio Vilches

Logconcave functions represent the current frontier of efficient algorithms for sampling, optimization and integration in R^n. Efficient sampling algorithms to sample according to a probability density (to which the other two problems can…

Data Structures and Algorithms · Computer Science 2009-06-16 Karthekeyan Chandrasekaran , Amit Deshpande , Santosh Vempala

This article proposes a new discrete framework for approximating solutions to shape optimization problems under convexity constraints. The numerical method, based on the support function or the gauge function, is guaranteed to generate…

Optimization and Control · Mathematics 2022-03-15 Beniamin Bogosel

A convex optimization problem in conic form involves minimizing a linear functional over the intersection of a convex cone and an affine subspace. In some cases, it is possible to replace a conic formulation using a certain cone, with a…

Optimization and Control · Mathematics 2019-08-06 James Saunderson

This paper determines the optimal upper bound for the simultaneous packing and covering constants of the two-dimensional centrally symmetric convex domains. It solved a problem opening for more than thirty years.

Metric Geometry · Mathematics 2007-06-14 Chuanming Zong

In the monotone integer dualization problem, we are given two sets of vectors in an integer box such that no vector in the first set is dominated by a vector in the second. The question is to check if the two sets of vectors cover the…

Discrete Mathematics · Computer Science 2024-08-14 Khaled Elbassioni

To determine the dimension of null space of any given linearized polynomial is one of vital problems in finite field theory, with concern to design of modern symmetric cryptosystems. But, the known general theory for this task is much far…

Information Theory · Computer Science 2018-11-29 Sihem Mesnager , Kwang Ho Kim , Myong Song Jo

We show that a nontrivial graph isomorphism problem of two undirected graphs, and more generally, the permutation similarity of two given $n\times n$ matrices, is equivalent to equalities of volumes of the induced three convex bounded…

Computational Complexity · Computer Science 2009-11-10 Shmuel Friedland

We apply polynomial techniques (linear programming) to obtain lower and upper bounds on the covering radius of spherical designs as function of their dimension, strength, and cardinality. In terms of inner products we improve the lower…

Combinatorics · Mathematics 2020-07-14 Peter Boyvalenkov , Maya Stoyanova

We are interested in the optimization of convex domains under a PDE constraint. Due to the difficulties of approximating convex domains in $\mathbb{R}^3$, the restriction to rotationally symmetric domains is used to reduce shape…

Optimization and Control · Mathematics 2022-06-13 Hedwig Keller , Sören Bartels , Gerd Wachsmuth

We classify, according to their computational complexity, integer optimization problems whose constraints and objective functions are polynomials with integer coefficients and the number of variables is fixed. For the optimization of an…

Optimization and Control · Mathematics 2017-01-03 Jesús A. De Loera , Raymond Hemmecke , Matthias Köppe , Robert Weismantel

This paper considers the problem of smoothing convex functions and sets, seeking the nearest smooth convex function or set to a given one. For convex cones and sublinear functions, a full characterization of the set of all optimal…

Optimization and Control · Mathematics 2025-08-22 Thabo Samakhoana , Benjamin Grimmer

In this paper, we investigate the polyhedral structure of two submodular sets with generalized upper bound (GUB) constraints, which arise as important substructures in various real-world applications. We derive a class of strong valid…

Optimization and Control · Mathematics 2026-01-27 Weikang Qian , Keyan Li , Wei-Kun Chen , Yu-Hong Dai

Our main result is that every n-dimensional polytope can be described by at most (2n-1) polynomial inequalities and, moreover, these polynomials can explicitly be constructed. For an n-dimensional pointed polyhedral cone we prove the bound…

Metric Geometry · Mathematics 2007-05-23 Hartwig Bosse , Martin Groetschel , Martin Henk

We consider two well-known problems: upper bounding the volume of lower dimensional ellipsoids contained in convex bodies given their John ellipsoid, and lower bounding the volume of ellipsoids containing projections of convex bodies given…

Metric Geometry · Mathematics 2025-01-03 René Brandenberg , Florian Grundbacher

Continuous, dually epi-translation invariant valuations on the space of finite-valued convex functions on $\mathbb{C}^n$ that are invariant under the unitary group are investigated. It is shown that elements belonging to the dense subspace…

Metric Geometry · Mathematics 2026-01-27 Jonas Knoerr

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

We provide three new proofs of the strong concavity of the dual function of some convex optimization problems. For problems with nonlinear constraints, we show that the the assumption of strong convexity of the objective cannot be weakened…

Optimization and Control · Mathematics 2021-05-04 Vincent Guigues