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We give a systematic and thorough study of geometric notions and results connected to Minkowski's measure of symmetry and the extension of the well-known Minkowski functional to arbitrary, not necessarily symmetric convex bodies K on any…

Classical Analysis and ODEs · Mathematics 2007-05-23 Szilard Gy. Revesz

Many star bodies have convex subsets with approximately the same Gaussian measure (of the complement). Inspired by this phenomenon, and in connection with the randomized Dvoretzky theorem for Lorentz spaces, we derive bounds on the…

Functional Analysis · Mathematics 2022-06-22 Daniel J. Fresen

We briefly introduce several problems: (1) a generalization of the convex fair partition conjecture, (2) on non-trivial invariants among polyhedrons that can be formed from the same set of face polygons, (3) two questions on assembling…

Metric Geometry · Mathematics 2015-02-16 R. Nandakumar

We consider the Banach space consisting of continuous functions from an arbitrary uncountable compact metric space, $X$, into $\mathbb{R}^n$. The key question is `what is the generic dimension of $f(X)$?' and we consider two different…

Classical Analysis and ODEs · Mathematics 2019-06-10 Richárd Balka , Ábel Farkas , Jonathan M. Fraser , James T. Hyde

In this paper, we study the deformation of the intersection of one compact set with a closed neighborhood of another compact set by changing the radius of this neighborhood. It is shown that in finite-dimensional normed spaces, in the case…

Metric Geometry · Mathematics 2022-11-09 A. Kh. Galstyan

The study of convex functions - in particular, of their optimization (really minimization) is one of the most important fields of applied mathematics. Convexity seems to be one of those incredibly well-chosen hypotheses which is just…

Optimization and Control · Mathematics 2026-03-11 Eigil Fjeldgren Rischel

We develop a technique using dual mixed-volumes to study the isotropic constants of some classes of spaces. In particular, we recover, strengthen and generalize results of Ball and Junge concerning the isotropic constants of subspaces and…

Functional Analysis · Mathematics 2007-05-23 Emanuel Milman

Quasifuchsian hyperbolic manifolds, or more generally convex co-compact hyperbolic manifolds, have infinite volume, but they have a well-defined ``renormalized'' volume. We outline some relations between this renormalized volume and the…

Geometric Topology · Mathematics 2019-03-26 Jean-Marc Schlenker

We propose a new class of hypertopologies, called here weak$^{\ast }$ hypertopologies, on the dual space $\mathcal{X}^{\ast }$ of a real or complex topological vector space $\mathcal{X}$. The most well-studied and well-known hypertopology…

Functional Analysis · Mathematics 2021-03-16 J. -B. Bru , W. de Siqueira Pedra

We associate convex bodies to a wide class of graded G-algebras where G is a connected reductive group. These convex bodies give information about the Hilbert function as well as multiplicities of irreducible representations appearing in…

Algebraic Geometry · Mathematics 2012-03-30 Kiumars Kaveh , Askold G. Khovanskii

The aim of this paper is to demonstrate relations between Gromov-Hausdorff distance properties and the Borsuk Conjecture. The Borsuk number of a given bounded metric space $X$ is the infimum of cardinal numbers $n$ such that $X$ can be…

General Topology · Mathematics 2022-03-15 Alexander Ivanov , Alexey Tuzhilin

We use the intrinsic area to define a distance on the space of homothety classes of convex bodies in the $n$-dimensional Euclidean space, which makes it isometric to a convex subset of the infinite dimensional hyperbolic space. The ambient…

Differential Geometry · Mathematics 2021-09-02 Clément Debin , François Fillastre

We investigate certain envelopes of open sets in dual Banach spaces which are related to extending holomorphic functions. We give a variety of examples of absolutely convex sets showing that the extension is in many cases not possible. We…

Functional Analysis · Mathematics 2010-05-10 D. Garcia , O. F. K. Kalenda , M. Maestre

Using an optimal containment approach, we quantify the asymmetry of convex bodies in $\mathbb{R}^n$ with respect to reflections across affine subspaces of a given dimension. We prove general inequalities relating these ''Minkowski…

Approximating convex bodies is a fundamental question in geometry, which has a wide variety of applications. Given a convex body $K$ in $\textbf{R}^d$ for fixed $d$, the objective is to minimize the number of facets of an approximating…

Computational Geometry · Computer Science 2026-01-26 Sunil Arya , David M. Mount

The problem of minimizing the difference of two lower semicontinuous, proper, convex functions (a DC function) on a nonempty closed convex set in a locally convex Hausdorff topological vector space is studied in this paper. The focus is…

Optimization and Control · Mathematics 2024-12-02 Vu Thi Huong , Duong Thi Kim Huyen , Nguyen Dong Yen

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

We revisit an ingenious argument of K. Ball to provide sharp estimates for the volume of sections of a convex body in John's position. Our technique combines the geometric Brascamp-Lieb inequality with a generalised Parseval-type identity.…

Metric Geometry · Mathematics 2026-03-31 David Alonso-Gutiérrez , Silouanos Brazitikos , Giorgos Chasapis

With any convex function F on a finite-dimensional linear space X such that F goes to infinity at infinity, we associate a Borel measure on the dual space X*. This measure is obtained by pushing forward the measure exp(-F(x))dx under the…

Functional Analysis · Mathematics 2013-04-03 Dario Cordero-Erausquin , Bo'az Klartag

In general, approximating classes of functions defined over high-dimensional input spaces by linear combinations of a fixed set of basis functions or ``features'' is known to be hard. Typically, the worst-case error of the best basis set…

Machine Learning · Computer Science 2025-12-05 Jonathan Baxter , Peter Bartlett
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