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We discuss how well a given convex body B in a real d-dimensional vector space V can be approximated by a set X for which the membership question: ``given an x in V, does x belong to X?'' can be answered efficiently (in time polynomial in…

Metric Geometry · Mathematics 2007-05-23 Alexander Barvinok , Ellen Veomett

In this note we study the maximal perimeter of a convex set in $\mathbb{R}^n$ with respect to various classes of measures. Firstly, we show that for a probability measure $\mu$ on $ \mathbb{R}^n$, satisfying very mild assumptions, there…

Metric Geometry · Mathematics 2019-05-01 Galyna V. Livshyts

Shape constrained densities are encountered in many nonparametric estimation problems. The classes of monotone or convex (and monotone) densities can be viewed as special cases of the classes of k-monotone densities. A density g is said to…

Statistics Theory · Mathematics 2007-06-13 Fadoua Balabdaoui , Jon A. Wellner

The convex hull of N independent random points chosen on the boundary of a simple polytope in R^n is investigated. Asymptotic formulas for the expected number of vertices and facets, and for the expectation of the volume difference are…

Probability · Mathematics 2022-01-11 M. Reitzner , C. Schuett , E. M. Werner

We introduce a new variant of quantitative Helly-type theorems: the minimal \emph{"homothetic distance"} of the intersection of a family of convex sets to the intersection of a subfamily of a fixed size. As an application, we establish the…

Metric Geometry · Mathematics 2021-11-03 Grigory Ivanov , Márton Naszódi

We provide an affirmative answer to a problem posed by Barvinok and Veomett, showing that in general an n-dimensional convex body cannot be approximated by a projection of a section of a simplex of a sub-exponential dimension. Moreover, we…

Functional Analysis · Mathematics 2012-09-28 Alexander E. Litvak , Mark Rudelson , Nicole Tomczak-Jaegermann

This paper studies best finitely supported approximations of one-dimensional probability measures with respect to the $L^r$-Kantorovich (or transport) distance, where either the locations or the weights of the approximations' atoms are…

Probability · Mathematics 2019-03-06 Chuang Xu , Arno Berger

We show that the expected value of the mean width of a random polytope generated by $N$ random vectors ($n\leq N\leq e^{\sqrt n}$) uniformly distributed in an isotropic convex body in $\R^n$ is of the order $\sqrt{\log N} L_K$. This…

Functional Analysis · Mathematics 2012-05-29 David Alonso-Gutierrez , Joscha Prochno

Let $K$ be a convex body in $\mathbb{R} ^d$, with $d = 2,3$. We determine sharp sufficient conditions for a set $E$ composed of $1$, $2$, or $3$ points of ${\rm bd}K$, to contain at least one endpoint of a diameter of $K$ (for $d=2,3$). We…

Metric Geometry · Mathematics 2019-10-28 Jin-ichi Itoh , Costin Vîlcu , Liping Yuan , Tudor Zamfirescu

We introduce a rank-statistic approximation of $f$-divergences that avoids explicit density-ratio estimation by working directly with the distribution of ranks. For a resolution parameter $K$, we map the mismatch between two univariate…

Machine Learning · Statistics 2026-02-02 Viktor Stein , José Manuel de Frutos

The goal of this paper is to generalize the main results of [KM] and subsequent papers on metric Diophantine approximation with dependent quantities to the set-up of systems of linear forms. In particular, we establish `joint strong…

Number Theory · Mathematics 2011-06-10 Dmitry Kleinbock , Gregory Margulis , Junbo Wang

Conventional approximations to Bayesian inference rely on either approximations by statistics such as mean and covariance or by point particles. Recent advances such as the ensemble Gaussian mixture filter have generalized these notions to…

Optimization and Control · Mathematics 2025-04-10 Andrey A Popov

We prove upper bounds on the graph diameters of polytopes in two settings. The first is a worst-case bound for polytopes defined by integer constraints in terms of the height of the integers and certain subdeterminants of the constraint…

Combinatorics · Mathematics 2022-09-16 Hariharan Narayanan , Rikhav Shah , Nikhil Srivastava

Let $K$ be a centrally-symmetric convex body in $\mathbb{R}^n$ and let $\|\cdot\|$ be its induced norm on ${\mathbb R}^n$. We show that if $K \supseteq r B_2^n$ then: \[ \sqrt{n} M(K) \leqslant C \sum_{k=1}^{n} \frac{1}{\sqrt{k}}…

Functional Analysis · Mathematics 2016-02-02 Apostolos Giannopoulos , Emanuel Milman

Let $K$ and $K_0$ be convex bodies in $\mathbb{R}^d$, such that $K$ contains the origin, and define the process $(K_n, p_n)$, $n \geq 0$, as follows: let $p_{n+1}$ be a uniform random point in $K_n$, and set $K_{n+1} = K_n \cap (p_{n+1} +…

Probability · Mathematics 2014-06-26 Péter Kevei , Viktor Vígh

The Newton polytope $P_f$ of a polynomial $f$ is well known to have a strong impact on its zeros, as in the Kouchnirenko-Bernstein theorem on the number of simultaneous zeros of $m$ polynomials with given Newton polytopes. In this article,…

Algebraic Geometry · Mathematics 2007-05-23 Bernard Shiffman , Steve Zelditch

We show that the non-symmetric Banach-Mazur distance between two convex bodies $K_1, K_2 \subseteq \mathbb{R}^n$ satisfies $$ d_{BM}(K_1, K_2) \leq C n \cdot \log^{\alpha} (n+1), $$ for universal constants $C, \alpha > 0$. This improves…

Metric Geometry · Mathematics 2025-11-06 Pierre Bizeul , Boaz Klartag

We prove that if a rectangular matrix with uniformly small entries and approximately orthogonal rows is applied to the independent standardized random variables with uniformly bounded third moments, then the empirical CDF of the resulting…

Probability · Mathematics 2007-06-14 Bernard Bercu , Wlodzimierz Bryc

Suppose that $\ff \in \reals^{n}$ is a vector of $n$ error-contaminated measurements of $n$ smooth values measured at distinct and strictly ascending abscissae. The following projective technique is proposed for obtaining a vector of smooth…

Numerical Analysis · Computer Science 2010-07-27 M. P. Cullinan

We develop polynomial-time algorithms for near-optimal minimax mean estimation under $\ell_2$-squared loss in a Gaussian sequence model under convex constraints. The parameter space is an origin-symmetric, type-2 convex body $K \subset…

Statistics Theory · Mathematics 2026-02-27 Matey Neykov
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