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We extend recent higher order concentration results in the discrete setting to include functions of possibly dependent variables whose distribution (on the product space) satisfies a logarithmic Sobolev inequality with respect to a…

Probability · Mathematics 2020-05-15 Friedrich Götze , Holger Sambale , Arthur Sinulis

We give a distribution-dependent concentration inequality for functions of independent variables. The result extends Bernstein's inequality from sums to more general functions, whose variation in any argument does not depend too much on the…

Probability · Mathematics 2017-05-12 Andreas Maurer

We establish the first extension results for divergence-free (or solenoidal) elements of $\mathrm{L}^{1}$-based function spaces. Here, the key point is to preserve the solenoidality constraint while simultaneously keeping the underlying…

Analysis of PDEs · Mathematics 2024-08-09 Franz Gmeineder , Stefan Schiffer

Many random combinatorial objects have a component structure whose joint distribution is equal to that of a process of mutually independent random variables, conditioned on the value of a weighted sum of the variables. It is interesting to…

Probability · Mathematics 2013-08-16 Richard Arratia , Simon Tavare

We obtain bounds on fluctuations of two entropy estimators for a class of one-dimensional Gibbs measures on the full shift. They are the consequence of a general exponential inequality for Lipschitz functions of n variables. The first…

Dynamical Systems · Mathematics 2015-05-27 J. -R. Chazottes , C. Maldonado

Given a family of locally Lipschitz vector fields $X(x)=(X_1(x),\dots,X_m(x))$ on $\mathbb{R}^n$, $m\leq n$, we study integral functionals depending on $X$. Using the results in \cite{MPSC1}, we study the convergence of minima, minimizers…

Analysis of PDEs · Mathematics 2022-11-08 Alberto Maione , Andrea Pinamonti , Francesco Serra Cassano

The classical Gaussian concentration inequality for Lipschitz functions is adapted to a setting where the classical assumptions (i.e. Lipschitz and Gaussian) are not met. The theory is more direct than much of the existing theory designed…

Probability · Mathematics 2022-05-16 Daniel J. Fresen

We construct meta-intransitive systems of independent random variables of any finite order from basic tuple of random variables which generalize intransitive dice. Under this construction, the equality of some linear functional is…

Probability · Mathematics 2024-05-07 Alexey V. Lebedev

New Vapnik and Chervonenkis type concentration inequalities are derived for the empirical distribution of an independent random sample. Focus is on the maximal deviation over classes of Borel sets within a low probability region. The…

Statistics Theory · Mathematics 2022-04-26 Stéphane Lhaut , Anne Sabourin , Johan Segers

In this paper, we consider a concentration of measure problem on Riemannian manifolds with boundary. We study concentration phenomena of non-negative $1$-Lipschitz functions with Dirichlet boundary condition around zero, which is called…

Metric Geometry · Mathematics 2018-08-17 Yohei Sakurai

We prove generalized Gaffney inequalities and the discrete compactness for finite element differential forms on $s$-regular domains, including general Lipschitz domains. In computational electromagnetism, special cases of these results have…

Numerical Analysis · Mathematics 2018-07-18 Juncai He , Kaibo Hu , Jinchao Xu

We propose a new length formula that governs the iterates of the momentum method when minimizing differentiable semialgebraic functions with locally Lipschitz gradients. It enables us to establish local convergence, global convergence, and…

Optimization and Control · Mathematics 2024-01-09 Cédric Josz , Lexiao Lai , Xiaopeng Li

In this note, we obtain a Gaussian concentration inequality for a class of non-Lipschitz functions. In the one-dimensional case, our results supplement those established by Paouris and Valettas in [8].

Probability · Mathematics 2022-07-11 Nguyen Tien Dung

We derive some estimates for the integral modulus of continuity of probability densities of infinitely divisible distributions. The paper is splitted into two parts. The first part deals with general infinitely divisible distributions. The…

Probability · Mathematics 2018-05-07 David Berger

We consider random fields that can be represented as integrals of deterministic functions with respect to infinitely divisible random measures and show that these random fields are infinitely divisible.

Probability · Mathematics 2010-08-13 Wolfgang Karcher , Hans-Peter Scheffler , Evgeny Spodarev

We discuss the identification of a time-dependent potential in a time-fractional diffusion model from a boundary measurement taken at a single point. Theoretically, we establish a conditional Lipschitz stability for this inverse problem.…

Numerical Analysis · Mathematics 2024-07-23 Siyu Cen , Kwancheol Shin , Zhi Zhou

We prove that intersections and unions of independent random sets in finite spaces achieve a form of Lipschitz continuity. More precisely, given the distribution of a random set $\Xi$, the function mapping any random set distribution to the…

Other Statistics · Statistics 2020-03-03 John Klein

The fundamental relaxation result for Lipschitz differential inclusions is the Filippov-Wazewski Relaxation Theorem, which provides approximations of trajectories of a relaxed inclusion on finite intervals. A complementary result is…

Dynamical Systems · Mathematics 2007-05-23 Brian Ingalls , Eduardo D. Sontag , Yuan Wang

Following the concentration of the measure theory formalism, we consider the transformation $\Phi(Z)$ of a random variable $Z$ having a general concentration function $\alpha$. If the transformation $\Phi$ is $\lambda$-Lipschitz with…

Probability · Mathematics 2026-02-03 Cosme Louart

There has been a surge of works bridging MCMC sampling and optimization, with a specific focus on translating non-asymptotic convergence guarantees for optimization problems into the analysis of Langevin algorithms in MCMC sampling. A…

Machine Learning · Computer Science 2021-10-06 Yoav Freund , Yi-An Ma , Tong Zhang