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In contrast to existing works on stochastic averaging on finite intervals, we establish an averaging principle on the whole real axis, i.e. the so-called second Bogolyubov theorem, for semilinear stochastic ordinary differential equations…

Dynamical Systems · Mathematics 2020-03-27 David Cheban , Zhenxin Liu

Non-asymptotic bounds for Gaussian and bootstrap approximation have recently attracted significant interest in high-dimensional statistics. This paper studies Berry-Esseen bounds for such approximations with respect to the multivariate…

Statistics Theory · Mathematics 2022-02-08 Miles E. Lopes

We derive normal approximation bounds in the Wasserstein distance for sums of weighted U-statistics, based on a general distance bound for functionals of independent random variables of arbitrary distributions. Those bounds are applied to…

Probability · Mathematics 2020-07-28 Nicolas Privault , Grzegorz Serafin

This paper presents new uniform Gaussian strong approximations for empirical processes indexed by classes of functions based on $d$-variate random vectors ($d\geq1$). First, a uniform Gaussian strong approximation is established for general…

Statistics Theory · Mathematics 2024-11-14 Matias D. Cattaneo , Ruiqi Rae Yu

We propose a second-order (Hessian or Hessian-free) based optimization method for variational inference inspired by Gaussian backpropagation, and argue that quasi-Newton optimization can be developed as well. This is accomplished by…

Machine Learning · Statistics 2017-03-30 Kai Fan , Ziteng Wang , Jeff Beck , James Kwok , Katherine Heller

We prove a new general Poincar\'e-type inequality for differential forms on compact Riemannian manifolds with nonempty boundary. When the boundary is isometrically immersed in Euclidean space, we derive a new inequality involving mean and…

Differential Geometry · Mathematics 2023-11-09 Nicolas Ginoux , Georges Habib , Simon Raulot

Let $V$ be a locally bounded measurable function such that $e^{-V}$ is bounded and belongs to $L^1(dx)$, and let $\mu_V(dx):=C_V e^{-V(x)} dx$ be a probability measure. We present the criterion for the weighted Poincar\'{e} inequality of…

Probability · Mathematics 2012-08-01 Xin Chen , Jian Wang

We propose a sampling algorithm that achieves superior complexity bounds in all the classical settings (strongly log-concave, log-concave, Logarithmic-Sobolev inequality (LSI), Poincar\'e inequality) as well as more general settings with…

Statistics Theory · Mathematics 2023-06-29 Jiaojiao Fan , Bo Yuan , Yongxin Chen

We develop a unified strategy to obtain the geometric logarithmic Hardy inequality on any open set M of a stratified group, provided the validity of the Hardy inequality in this setting, where the so-called "weight" is regarded to be any…

Functional Analysis · Mathematics 2024-02-19 Marianna Chatzakou

This note describes non-asymptotic variance and tail bounds for order statistics of samples of independent identically distributed random variables. Those bounds are checked to be asymptotically tight when the sampling distribution belongs…

Probability · Mathematics 2012-11-05 Stephane Boucheron , Maud Thomas

In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak--Ruppert averaged iterates generated by entropy-regularized asynchronous Q-learning with linear function approximation and a polynomial…

Machine Learning · Statistics 2026-05-19 Artemy Rubtsov , Rahul Singh , Eric Moulines , Alexey Naumov , Sergey Samsonov

We investigate the use of a certain class of functional inequalities known as weak Poincar\'e inequalities to bound convergence of Markov chains to equilibrium. We show that this enables the straightforward and transparent derivation of…

Computation · Statistics 2024-09-25 Christophe Andrieu , Anthony Lee , Sam Power , Andi Q. Wang

The aim of this paper is to establish various functional inequalities for the convolution of a compactly supported measure and a standard Gaussian distribution on Rd. We especially focus on getting good dependence of the constants on the…

Probability · Mathematics 2015-07-10 Jean-Baptiste Bardet , Nathaël Gozlan , Florent Malrieu , Pierre-André Zitt

We study rates of convergence for estimation of the Gromov-Wasserstein (GW) distance. For two marginals supported on compact subsets of $\R^{d_x}$ and $\R^{d_y}$, respectively, with $\min \{ d_x,d_y \} > 4$, prior work established the rate…

Statistics Theory · Mathematics 2025-09-03 Kengo Kato , Boyu Wang

In this work a local inequality is provided which bounds the distance of an integral varifold from a multivalued plane (height) by its tilt and mean curvature. The bounds obtained for the exponents of the Lebesgue spaces involved are shown…

Differential Geometry · Mathematics 2012-01-05 Ulrich Menne

We prove a Poincar\'e-Sobolev type inequality on compact Riemannian manifolds where the deviation of a function from a biased average, defined using a density, is controlled by the unweighted Lebesgue norm of its gradient. Unlike classical…

Analysis of PDEs · Mathematics 2025-12-22 Romain Gicquaud

We extend the Malliavin theory for $L^2$-functionals on product probability spaces that has recently been developed by Decreusefond and Halconruy (2019) and by Duerinckx (2021), by characterizing the domains and investigating the actions of…

Probability · Mathematics 2024-03-25 Christian Döbler

We obtain a Bernstein type Gaussian concentration inequality for martingales. Our inequality improves the Azuma-Hoeffding inequality for moderate deviations $x$. Following the work of McDiarmid (1989), Talagrand (1996) and Boucheron, Lugosi…

Probability · Mathematics 2017-10-17 Xiequan Fan

Let $\varepsilon_1,\ldots,\varepsilon_n$ be independent identically distributed Rademacher random variables, that is $\mathbb{P}\{\varepsilon_i=\pm1\}=1/2$. Let $S_n=a_1\varepsilon_1+\cdots+a_n\varepsilon_n$, where…

Probability · Mathematics 2015-06-02 Vidmantas Kastytis Bentkus , Dainius Dzindzalieta

The purpose of this paper is to analyze the distribution distance between random vectors derived from the magnitude of the analytic wavelet transform of the squared envelopes of Gaussian processes and their large-scale limits. When the…

Probability · Mathematics 2024-09-05 Gi-Ren Liu