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Related papers: Universal Barrier is $n$-Self-Concordant

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We prove that the Cram\'er transform of the uniform measure on a convex body in $\mathbb{R}^n$ is a $(1+o(1)) n$-self-concordant barrier, improving a seminal result of Nesterov and Nemirovski. This gives the first explicit construction of a…

Optimization and Control · Mathematics 2015-04-14 Sébastien Bubeck , Ronen Eldan

For any convex body $K \subseteq \mathbb R^n$, S. Bubeck and R. Eldan introduced the entropic barrier on $K$ and showed that it is a $(1+o(1)) \, n$-self-concordant barrier. In this note, we observe that the optimal bound of $n$ on the…

Metric Geometry · Mathematics 2021-12-22 Sinho Chewi

Quantum relative entropies are jointly convex functions of two positive definite matrices that generalize the Kullback-Leibler divergence and arise naturally in quantum information theory. In this paper, we prove self-concordance of natural…

Optimization and Control · Mathematics 2023-02-21 Hamza Fawzi , James Saunderson

In this paper we theoretically show that interior-point methods based on self-concordant barriers possess favorable global complexity beyond their standard application area of convex optimization. To do that we propose first- and…

Optimization and Control · Mathematics 2024-04-30 Pavel Dvurechensky , Mathias Staudigl

Interior-point methods offer a highly versatile framework for convex optimization that is effective in theory and practice. A key notion in their theory is that of a self-concordant barrier. We give a suitable generalization of…

Optimization and Control · Mathematics 2024-06-26 Hiroshi Hirai , Harold Nieuwboer , Michael Walter

Self-concordant barriers are essential for interior-point algorithms in conic programming. To speed up the convergence it is of interest to find a barrier with the lowest possible parameter for a given cone. The barrier parameter is a…

Optimization and Control · Mathematics 2025-07-08 Vitali Pirau , Roland Hildebrand

We obtain a new upper bound for Neumann eigenvalues of the Laplacian on a bounded convex domain in Euclidean space. As an application of the upper bound we derive universal inequalities for Neumann eigenvalues of the Laplacian.

Spectral Theory · Mathematics 2023-11-08 Kei Funano

The article contains the results of the author's recent investigations of rigidity problems of domains in Euclidean spaces carried out for developing a new approach to the classical problem of the unique determination of bounded closed…

Metric Geometry · Mathematics 2016-10-05 Anatoly P. Kopylov

In 2021, Ordentlich, Regev and Weiss made a breakthrough that the lattice covering density of any $n$-dimensional convex body is upper bounded by $cn^{2}$, improving on the best previous bound established by Rogers in 1959. However, for the…

Metric Geometry · Mathematics 2025-06-04 Matthias Schymura , Jun Wang , Fei Xue

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

We prove that the highest density of non-overlapping translates of a given centrally symmetric convex domain relative to its outer parallel domain of given outer radius is attained by a lattice packing in the Euclidean plane. This…

Metric Geometry · Mathematics 2025-12-30 Károly Bezdek , Zsolt Lángi

Constrained diffusions in convex polyhedral domains with a general oblique reflection field, and with a diffusion coefficient scaled by a small parameter, are considered. Using an interior Dirichlet heat kernel lower bound estimate for…

Probability · Mathematics 2013-08-19 Amarjit Budhiraja , Zhen-Qing Chen

Barrier methods play a central role in the theory and practice of convex optimization. One of the most general and successful analyses of barrier methods for convex optimization, due to Nesterov and Nemirovskii, relies on the notion of…

Optimization and Control · Mathematics 2025-02-11 Kerry He , James Saunderson , Hamza Fawzi

We provide a sharp lower bound for the perimeter of the inner parallel sets of a convex body $\Omega$. The bound depends only on the perimeter and inradius $r$ of the original body and states that \[|\partial\Omega_t| \geq…

Metric Geometry · Mathematics 2020-05-05 Simon Larson

Let $K$ be a convex body (a non-empty compact convex set) in $n$-dimensional Euclidean space. A set $B$ is called a barrier (or an `opaque set') for $K$ if every line that intersects $K$, also intersects $B$. Although this concept was…

Metric Geometry · Mathematics 2026-05-14 Markus Kiderlen

In this paper, we obtain optimal upper bounds for all the Neumann eigenvalues in two situations (that are closely related). First we consider a one-dimensional Sturm-Liouville eigenvalue problem where the density is a function $h(x)$ whose…

Analysis of PDEs · Mathematics 2022-12-01 Antoine Henrot , Marco Michetti

A small polygon is a polygon of unit diameter. The maximal perimeter and the maximal width of a convex small polygon with $n=2^s$ vertices are not known when $s \ge 4$. In this paper, we construct a family of convex small $n$-gons, $n=2^s$…

Optimization and Control · Mathematics 2022-12-27 Christian Bingane

We prove a sharp upper bound on convex domains, in terms of the diameter alone, of the best constant in a class of weighted Poincar\'e inequalities. The key point is the study of an optimal weighted Wirtinger inequality.

Optimization and Control · Mathematics 2012-11-07 Vincenzo Ferone , Carlo Nitsch , Cristina Trombetti

Motivated by the Dikin walk, we develop aspects of an interior-point theory for sampling in high dimension. Specifically, we introduce a symmetric parameter and the notion of strong self-concordance. These properties imply that the…

Data Structures and Algorithms · Computer Science 2020-07-13 Aditi Laddha , Yin Tat Lee , Santosh Vempala

In this paper, we address an extension of the theory of self-concordant functions for a manifold. We formulate the self-concordance of a geodesically convex function by a condition of the covariant derivative of its Hessian, and verify that…

Optimization and Control · Mathematics 2023-04-18 Hiroshi Hirai
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