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Intrinsic volumes, which generalize both Euler characteristic and Lebesgue volume, are important properties of $d$-dimensional sets. A random cubical complex is a union of unit cubes, each with vertices on a regular cubic lattice,…

Probability · Mathematics 2021-08-24 Michael Werman , Matthew L. Wright

We study the problem of finding the Lowner-John ellipsoid, i.e., an ellipsoid with minimum volume that contains a given convex set. We reformulate the problem as a generalized copositive program, and use that reformulation to derive…

Optimization and Control · Mathematics 2020-06-22 Areesh Mittal , Grani A. Hanasusanto

We give a deterministic 2^{O(n)} algorithm for computing an M-ellipsoid of a convex body, matching a known lower bound. This has several interesting consequences including improved deterministic algorithms for volume estimation of convex…

Computational Complexity · Computer Science 2014-03-05 Daniel Dadush , Santosh Vempala

We consider a multidimensional search problem that is motivated by questions in contextual decision-making, such as dynamic pricing and personalized medicine. Nature selects a state from a $d$-dimensional unit ball and then generates a…

Data Structures and Algorithms · Computer Science 2017-04-27 Ilan Lobel , Renato Paes Leme , Adrian Vladu

It is shown that Alesker's solution of McMullen's conjecture implies the following stronger version of the conjecture: Every continuous, translation invariant, $k$-homogeneous valuation on convex bodies in $\mathbb{R}^n$ can be approximated…

Metric Geometry · Mathematics 2024-10-16 Jonas Knoerr

We present a technique for reducing the computational requirements by several orders of magnitude in the evaluation of semidefinite relaxations for bounding the set of quantum correlations arising from finite-dimensional Hilbert spaces. The…

Quantum Physics · Physics 2019-02-22 Armin Tavakoli , Denis Rosset , Marc-Olivier Renou

Volume polynomials form a distinguished class of log-concave polynomials with remarkable analytic and combinatorial properties. I will survey realization problems related to them, review fundamental inequalities they satisfy, and discuss…

Algebraic Geometry · Mathematics 2026-02-02 June Huh

This paper introduces a natural definition for the volume of the unit ball in $n$-dimensional normed spaces $\mathbb{R}^n$. This definition preserves the Euclidean relation $P(B)/V(B)=n$ between the perimiter and the volume of the unit ball…

Metric Geometry · Mathematics 2026-05-05 Gershon Wolansky

In this paper, by means of a standard model problem, we devise an approach to computing approximate dual bounds for use in global optimization of coefficient identification in partial differential equations (PDEs) by, e.g., (spatial)…

Numerical Analysis · Mathematics 2026-03-20 Barbara Kaltenbacher , Paul Manns

The volume is an important attribute of a convex body. In general, it is quite difficult to calculate the exact volume. But in many cases, it suffices to have an approximate value. Volume estimation methods for convex bodies have been…

Computational Geometry · Computer Science 2014-01-03 Cunjing Ge , Feifei Ma , Jian Zhang

Estimating the volume of a convex body is a canonical problem in theoretical computer science. Its study has led to major advances in randomized algorithms, Markov chain theory, and computational geometry. In particular, determining the…

Quantum Physics · Physics 2025-03-05 Arjan Cornelissen , Simon Apers , Sander Gribling

We introduce a general framework for the construction of well-balanced finite volume methods for hyperbolic balance laws. We use the phrase well-balancing in a broader sense, since our proposed method can be applied to exactly follow any…

Numerical Analysis · Mathematics 2020-08-05 Jonas P. Berberich , Praveen Chandrashekar , Christian Klingenberg

We study the problem of approximating the mixed volume $V(P_1^{(\alpha_1)}, \dots, P_k^{(\alpha_k)})$ of an $k$-tuple of convex polytopes $(P_1, \dots, P_k)$, each of which is defined as the convex hull of at most $m_0$ points in…

Computational Geometry · Computer Science 2025-12-30 Hariharan Narayanan , Sourav Roy

We study the quantitative relationship between the cones of nonnegative polynomials, cones of sums of squares and cones of sums of powers of linear forms. We derive bounds on the volumes (raised to the power reciprocal to the ambient…

Algebraic Geometry · Mathematics 2007-05-23 Grigoriy Blekherman

A classical theorem of Macbeath states that for any integers $d \geq 2$, $n \geq d+1$, $d$-dimensional Euclidean balls are hardest to approximate, in terms of volume difference, by inscribed convex polytopes with $n$ vertices. In this paper…

Metric Geometry · Mathematics 2025-12-30 Z. Lángi , S. Wang

The problem of determining the volume of a tubular neighbourhood has a long and rich history. Bounds on the volume of neighbourhoods of algebraic sets have turned out to play an important role in the probabilistic analysis of condition…

Numerical Analysis · Mathematics 2013-10-01 Martin Lotz

Motivated by understanding the quality of tractable convex relaxations of intractable polytopes, Ko et al. gave a closed-form expression for the volume of a standard relaxation $\mathscr{Q}(G)$ of the boolean quadric polytope (also known as…

Combinatorics · Mathematics 2018-10-18 Jon Lee , Daphne Skipper

We study the relationship between the tensor product multiplicities of a compact semisimple Lie algebra $\mathfrak{g}$ and a special function $\mathcal{J}$ associated to $\mathfrak{g}$, called the volume function. The volume function arises…

Combinatorics · Mathematics 2020-04-28 Colin McSwiggen

We consider the chance-constrained binary knapsack problem (CKP), where the item weights are independent and normally distributed. We introduce a continuous relaxation for the CKP, represented as a non-convex optimization problem, which we…

Optimization and Control · Mathematics 2024-03-12 Junyoung Kim , Kyungsik Lee

Hyperbolic spaces have increasingly been recognized for their outstanding performance in handling data with inherent hierarchical structures compared to their Euclidean counterparts. However, learning in hyperbolic spaces poses significant…

Machine Learning · Computer Science 2024-05-28 Sheng Yang , Peihan Liu , Cengiz Pehlevan