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We sharpen the moment comparison inequalities with sharp constants for sums of random vectors uniform on Euclidean spheres, providing a deficit term (optimal in high dimensions).

Probability · Mathematics 2026-03-05 Jacek Jakimiuk , Colin Tang , Tomasz Tkocz

We consider sequences of $U$-processes based on symmetric kernels of a fixed order, that possibly depend on the sample size. Our main contribution is the derivation of a set of analytic sufficient conditions, under which the aforementioned…

Probability · Mathematics 2022-03-16 Christian Döbler , Mikołaj Kasprzak , Giovanni Peccati

We consider sequences of symmetric $U$-statistics, not necessarily Hoeffding-degenerate, both in a one- and multi-dimensional setting, and prove quantitative central limit theorems (CLTs) based on the use of {\it contraction operators}. Our…

Probability · Mathematics 2021-04-01 Christian Döbler , Giovanni Peccati

We study (asymmetric) $U$-statistics based on a stationary sequence of $m$-dependent variables; moreover, we consider constrained $U$-statistics, where the defining multiple sum only includes terms satisfying some restrictions on the gaps…

Probability · Mathematics 2022-03-10 Svante Janson

A general method for obtaining moment inequalities for functions of independent random variables is presented. It is a generalization of the entropy method which has been used to derive concentration inequalities for such functions…

Probability · Mathematics 2007-05-23 Stephane Boucheron , Olivier Bousquet , Gabor Lugosi , Pascal Massart

We consider the problem of bounding large deviations for non-i.i.d. random variables that are allowed to have arbitrary dependencies. Previous works typically assumed a specific dependence structure, namely the existence of independent…

Probability · Mathematics 2018-11-06 Christoph H. Lampert , Liva Ralaivola , Alexander Zimin

Convergence rates results for Tikhonov regularization of nonlinear ill-posed operator equations in abstract function spaces require the handling of both smoothness conditions imposed on the solution and structural conditions expressing the…

Numerical Analysis · Mathematics 2009-09-29 Radu Ioan Bot , Bernd Hofmann

We establish a simple variance inequality for U-statistics whose underlying sequence of random variables is an ergodic Markov Chain. The constants in this inequality are explicit and depend on computable bounds on the mixing rate of the…

Statistics Theory · Mathematics 2013-03-05 Gersende Fort , Eric Moulines , Pierre Priouret , Pierre Vandekerkhove

This paper establishes limit theorems and quantitative statistical stability for a class of piecewise partially hyperbolic maps that are not necessarily continuous nor locally invertible. By employing a flexible functional-analytic…

Dynamical Systems · Mathematics 2026-02-20 Rafael A. Bilbao , Rafael Lucena

In this paper we give new deviation inequalities of Bernstein's type for the partial sums of weakly dependent time series. The loss from the independent case is studied carefully. We give non mixing examples such that dynamical systems and…

Probability · Mathematics 2011-10-20 Olivier Wintenberger

In this paper we give conditions under which sub differential limits can be better estimated.

Functional Analysis · Mathematics 2022-12-20 Taduri Srinivas Siva Rama Krishna Rao

We consider the effect of perturbations to a quasi-linear parabolic stochastic differential equation set in a UMD Banach space $X$. To be precise, we consider perturbations of the linear part, i.e. the term concerning a linear operator $A$…

Functional Analysis · Mathematics 2012-03-08 Sonja Cox , Erika Hausenblas

We derive novel concentration inequalities that bound the statistical error for a large class of stochastic optimization problems, focusing on the case of unbounded objective functions. Our derivations utilize the following key tools: 1) A…

Machine Learning · Statistics 2026-01-01 Jeremiah Birrell

This paper is concerned with Spearman's correlation matrices under large dimensional regime, in which the data dimension diverges to infinity proportionally with the sample size. We establish the central limit theorem for the linear…

Statistics Theory · Mathematics 2024-11-26 Hantao Chen , Cheng Wang

We consider the problem of finding, for a given quadratic measure of non-uniformity of a set of $N$ points (such as $L_2$ star-discrepancy or diaphony), the asymptotic distribution of this discrepancy for truly random points in the limit…

Computational Physics · Physics 2009-10-30 Andre van Hameren , Ronald Kleiss , Jiri Hoogland

Under some mild regularity on the normalizing sequence, we obtain necessary and sufficient conditions for the Strong Law of Large Numbers for (symmetrized) U-statistics. We also obtain nasc's for the a.s. convergence of series of an…

Probability · Mathematics 2014-11-17 Rafał Latała , Joel Zinn

We establish normal approximation in the Wasserstein metric for both non-degenerate and degenerate second-order U-statistics under cross-sectional dependence using Stein's method. For the non-degenerate case, our results extend recent…

Econometrics · Economics 2026-04-28 Weiguang Liu

In this paper we consider a branching particle system consisting of particles moving according to the Ornstein-Uhlenbeck process in R^d and undergoing a binary, supercritical branching with a constant rate \lambda>0. This system is known to…

Probability · Mathematics 2014-07-10 Radosław Adamczak , Piotr Miłoś

Laws of large numbers, starting from certain nonequilibrium measures, have been shown for the integrated current across a bond, and a tagged particle in one-dimensional symmetric nearest-neighbor simple exclusion [Ann. Inst. Henri Poincare…

Probability · Mathematics 2013-05-28 Sunder Sethuraman , S. R. S. Varadhan

This paper studies inference for the mean vector of a high-dimensional $U$-statistic. In the era of Big Data, the dimension $d$ of the $U$-statistic and the sample size $n$ of the observations tend to be both large, and the computation of…

Statistics Theory · Mathematics 2019-01-29 Xiaohui Chen , Kengo Kato