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We show that for any $1\leq p\leq\infty$, the family of random vectors uniformly distributed on hyperplane projections of the unit ball of $\ell_p^n$ verify the variance conjecture $$ \textrm{Var}\,|X|^2\leq C\max_{\xi\in…

Functional Analysis · Mathematics 2016-10-14 David Alonso-Gutiérrez , Jesús Bastero

It was shown by G. Pisier that any finite-dimensional normed space admits an $\alpha$-regular $M$-position, guaranteeing not only regular entropy estimates but moreover regular estimates on the diameters of minimal sections of its unit-ball…

Functional Analysis · Mathematics 2021-05-28 Emanuel Milman , Yuval Yifrach

Central limit theorems for the log-volume of a class of random convex bodies in $\mathbb{R}^n$ are obtained in the high-dimensional regime, that is, as $n\to\infty$. In particular, the case of random simplices pinned at the origin and…

Let $K$ be a convex body in $\mathbb{R}^d$ which slides freely in a ball. Let $K^{(n)}$ denote the intersection of $n$ closed half-spaces containing $K$ whose bounding hyperplanes are independent and identically distributed according to a…

Metric Geometry · Mathematics 2015-12-09 Ferenc Fodor , Daniel Hug , Ines Ziebarth

Let N > n, and denote by K the convex hull of N independent standard gaussian random vectors in an n-dimensional Euclidean space. We prove that with high probability, the isotropic constant of K is bounded by a universal constant. Thus we…

Metric Geometry · Mathematics 2007-05-23 Bo'az Klartag , Gady Kozma

We study the spectral norm of large rectangular random Toeplitz and circulant matrices with independent entries. For Toeplitz matrices, we show that the scaled norm converges to the norm of a bilinear operator defined via the pointwise…

Probability · Mathematics 2025-09-05 Alexei Onatski

A random spherical polytope $P_n$ in a spherically convex set $K \subset S^d$ as considered here is the spherical convex hull of $n$ independent, uniformly distributed random points in $K$. The behaviour of $P_n$ for a spherically convex…

Probability · Mathematics 2015-05-19 Imre Bárány , Daniel Hug , Matthias Reitzner , Rolf Schneider

Let X Nv(0, {\Lambda}) be a normal vector in v dimensions, where {\Lambda} is diagonal. With reference to the truncated distribution of X on the interior of a v-dimensional Euclidean ball, we completely prove a variance inequality and a…

Statistics Theory · Mathematics 2013-11-26 Rahul Mukerjee , S. H. Ong

In this note we link symplectic and convex geometry by relating two seemingly different open conjectures: a symplectic isoperimetric-type inequality for convex domains, and Mahler's conjecture on the volume product of centrally symmetric…

Metric Geometry · Mathematics 2015-01-14 Shiri Artstein-Avidan , Roman Karasev , Yaron Ostrover

We prove that if $K$ is a symmetric and isotropic convex body in $\mathbb{R}^n$, then $$\int_K\langle x,u\rangle^2\,dx\int_{K^\circ}\langle x,u\rangle^2\,dx\leq \left(\int_{B_2^n}\langle x,u\rangle^2\,dx\right)^2,\qquad\forall…

Metric Geometry · Mathematics 2026-05-26 Károly J. Böröczky , Konstantinos Patsalos , Christos Saroglou

Given any half-sided modular inclusion of standard subspaces, we show that the entropy function associated with the decreasing one-parameter family of translated standard subspaces is convex for any given (not necessarily smooth) vector in…

Mathematical Physics · Physics 2024-01-11 Fabio Ciolli , Roberto Longo , Alessio Ranallo , Giuseppe Ruzzi

We present a simple solution to a question posed by Candes, Romberg and Tao on the uniform uncertainty principle for Bernoulli random matrices. More precisely, we show that a rectangular k*n random subgaussian matrix (with k < n) has the…

Statistics Theory · Mathematics 2007-06-13 Shahar Mendelson , Alain Pajor , Nicole Tomczak-Jaegermann

While monotone operator theory is often studied on Hilbert spaces, many interesting problems in machine learning and optimization arise naturally in finite-dimensional vector spaces endowed with non-Euclidean norms, such as…

Optimization and Control · Mathematics 2025-08-26 Alexander Davydov , Saber Jafarpour , Anton V. Proskurnikov , Francesco Bullo

While there is extensive literature on approximation, deterministic as well as random, of general convex bodies $K$ in the symmetric difference metric, or other metrics arising from intrinsic volumes, very little is known for corresponding…

Metric Geometry · Mathematics 2025-08-25 Joscha Prochno , Carsten Schütt , Mathias Sonnleitner , Elisabeth M. Werner

We prove a randomized version of the generalized Urysohn inequality relating mean-width to the other intrinsic volumes. To do this, we introduce a stochastic approximation procedure that sees each convex body K as the limit of intersections…

Metric Geometry · Mathematics 2016-06-30 Grigoris Paouris , Peter Pivovarov

Having its origin in theoretical computer science, the Kannan-Lov\'asz-Simonovits (KLS) conjecture is one of the major open problems in asymptotic convex geometry and high-dimensional probability theory today. In this work, we establish a…

Probability · Mathematics 2020-03-26 David Alonso-Gutiérrez , Joscha Prochno , Christoph Thaele

Given two vectors in Euclidean space, how unlikely is it that a random vector has a larger inner product with the shorter vector than with the longer one? When the random vector has independent, identically distributed components, we…

Probability · Mathematics 2018-05-23 Manjunath Krishnapur , Sourav Sarkar

We investigate the asymptotic best approximation of a smooth, strictly convex body $K$ in $\mathbb{R}^d$ by inscribed polytopes with a restricted number of vertices under the intrinsic volume difference. We prove rigidity phenomena in both…

Metric Geometry · Mathematics 2026-02-24 Steven Hoehner

We consider a non-commutative polynomial in several independent $N$-dimensional random unitary matrices, uniformly distributed over the unitary, orthogonal or symmetric groups, and assume that the coefficients are $n$-dimensional matrices.…

Probability · Mathematics 2024-01-11 Charles Bordenave , Benoit Collins

A well-known result says that the Euclidean unit ball is the unique fixed point of the polarity operator. This result implies that if, in $\mathbb{R}^n$, the unit ball of some norm is equal to the unit ball of the dual norm, then the norm…

Functional Analysis · Mathematics 2019-04-10 Daniel Reem , Simeon Reich
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