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Related papers: Stein's method on the second Wiener chaos : 2-Wass…

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This work presents several expected generalization error bounds based on the Wasserstein distance. More specifically, it introduces full-dataset, single-letter, and random-subset bounds, and their analogues in the randomized subsample…

Machine Learning · Statistics 2022-03-29 Borja Rodríguez-Gálvez , Germán Bassi , Ragnar Thobaben , Mikael Skoglund

In this paper, we explore some links between transforms derived by Stein's method and concentration inequalities. In particular, we show that the stochastic domination of the zero bias transform of a random variable is equivalent to…

Probability · Mathematics 2022-11-24 Santiago Arenas-Velilla , Emilien Joly

Gradient flow in the 2-Wasserstein space is widely used to optimize functionals over probability distributions and is typically implemented using an interacting particle system with $n$ particles. Analyzing these algorithms requires showing…

Machine Learning · Computer Science 2026-03-27 Chandan Tankala , Dheeraj M. Nagaraj , Anant Raj

We use Stein's method to obtain a bound on the distance between scaled $p$-dimensional random walks and a $p$-dimensional (correlated) Brownian Motion. We consider dependence schemes including those in which the summands in scaled sums are…

Probability · Mathematics 2020-06-09 Mikołaj J. Kasprzak

In this paper we present a numerical scheme for stochastic differential equations based upon the Wiener chaos expansion. The approximation of a square integrable stochastic differential equation is obtained by cutting off the infinite chaos…

Probability · Mathematics 2019-06-05 Tony Huschto , Mark Podolskij , Sebastian Sager

Let $n \in \mathbb N$, let $\zeta_{n,1},...,\zeta_{n,n}$ be a sequence of independent random variables with $\mathbb E \zeta_{n,i}=0$ and $\mathbb E |\zeta_{n,i}|<\infty$ for each $i$, and let $\mu$ be an $\alpha$-stable distribution having…

Probability · Mathematics 2018-11-20 Lihu Xu

In this paper we propose tight upper and lower bounds for the Wasserstein distance between any two {{univariate continuous distributions}} with probability densities $p_1$ and $p_2$ having nested supports. These explicit bounds are…

Probability · Mathematics 2015-10-21 Christophe Ley , Gesine Reinert , Yvik Swan

We consider $M/Ph/n+M$ queueing systems in steady state. We prove that the Wasserstein distance between the stationary distribution of the normalized system size process and that of a piecewise Ornstein-Uhlenbeck (OU) process is bounded by…

Probability · Mathematics 2015-12-01 Anton Braverman , J. G. Dai

We compare Wiener chaos and stochastic collocation methods for linear advection-reaction-diffusion equations with multiplicative white noise. Both methods are constructed based on a recursive multi-stage algorithm for long-time integration.…

Numerical Analysis · Mathematics 2015-05-18 Zhongqiang Zhang , Michael V. Tretyakov , Boris Rozovskii , George E. Karniadakis

We combine Stein's method with a version of Malliavin calculus on the Poisson space. As a result, we obtain explicit Berry-Ess\'een bounds in Central Limit Theorems (CLTs) involving multiple Wiener-It\^o integrals with respect to a general…

Probability · Mathematics 2008-08-01 Giovanni Peccati , Josep Lluís Solé , Murad S. Taqqu , Frederic Utzet

As an application of Stein's method for Poisson approximation, we prove rates of convergence for the tail probabilities of two scan statistics that have been suggested for detecting local signals in sequences of independent random variables…

Probability · Mathematics 2015-05-29 Xiao Fang , David Siegmund

In this paper, following Nourdin-Peccati's methodology, we combine the Malliavin calculus and Stein's method to provide general bounds on the Wasserstein distance between functionals of a compound Hawkes process and a given Gaussian…

Probability · Mathematics 2021-04-06 Caroline Hillairet , Lorick Huang , Mahmoud Khabou , Anthony Reveillac

In this paper we introduce a Wasserstein-type distance on the set of Gaussian mixture models. This distance is defined by restricting the set of possible coupling measures in the optimal transport problem to Gaussian mixture models. We…

Optimization and Control · Mathematics 2020-06-15 Julie Delon , Agnes Desolneux

We consider additive functionals of systems of random measures whose initial configuration is given by a Poisson point process, and whose individual components evolve according to arbitrary Markovian or non-Markovian measure valued…

Probability · Mathematics 2025-12-03 Arturo Jaramillo , Antonio Murillo-Salas

We use the Stein-Chen method to prove new explicit inequalities for the total variation, Wasserstein and local distances between the distribution of a random diagonal sum of a Bernoulli matrix and a Poisson distribution. Approximation…

Probability · Mathematics 2024-09-04 Bero Roos

Edgeworth expansion provides higher-order corrections to the normal approximation for a probability distribution. The classical proof of Edgeworth expansion is via characteristic functions. As a powerful method for distributional…

Probability · Mathematics 2022-11-09 Xiao Fang , Song-Hao Liu

Stein's method is used to approximate sums of discrete and locally dependent random variables by a centered and symmetric Binomial distribution. Under appropriate smoothness properties of the summands, the same order of accuracy as in the…

Probability · Mathematics 2007-05-23 Adrian Röllin

Let $\{X_{i}, i\in J\}$ be a family of locally dependent non-negative integer-valued random variables with finite expectations and variances. We consider the sum $W=\sum_{i\in J}X_i$ and use Stein's method to establish general upper error…

Probability · Mathematics 2024-11-26 Zhonggen Su , Xiaolin Wang

In this paper we obtain non-uniform Berry-Esseen bounds for normal approximations by the Malliavin-Stein method. The techniques rely on a detailed analysis of the solutions of Stein's equations and will be applied to functionals of a…

Probability · Mathematics 2024-09-17 Marius Butzek , Peter Eichelsbacher

We introduce a version of Stein's method for proving concentration and moment inequalities in problems with dependence. Simple illustrative examples from combinatorics, physics, and mathematical statistics are provided.

Probability · Mathematics 2007-05-23 Sourav Chatterjee