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In this paper, the boundary flex control problem of non stationary equation governing the coupled mass and heat flow of a viscous incompressible fluid in a generalized Boussinesq approximation by assuming that viscosity and heat…

Analysis of PDEs · Mathematics 2012-07-18 Gol Kim

A bilateral (i.e., upper and lower) bound on the mean-square error under a general model mismatch is developed. The bound, which is derived from the variational representation of the chi-square divergence, is applicable in the Bayesian and…

Signal Processing · Electrical Eng. & Systems 2023-05-16 Amir Weiss , Alejandro Lancho , Yuheng Bu , Gregory W. Wornell

New lower bounds on the total variation distance between the distribution of a sum of independent Bernoulli random variables and the Poisson random variable (with the same mean) are derived via the Chen-Stein method. The new bounds rely on…

Information Theory · Computer Science 2013-07-17 Igal Sason

Berry-Esseen bounds for non-linear functionals of infinite Rademacher sequences are derived by means of the Malliavin-Stein method. Moreover, multivariate extensions for vectors of Rademacher functionals are shown. The results establish a…

Probability · Mathematics 2017-11-06 Kai Krokowski , Anselm Reichenbachs , Christoph Thaele

In the present paper, we derive Berry-Esseen bounds for the estimation of diversity indices on countable alphabets. A general non-asymptotic convergence rate is established for the plug-in estimator of a wide class of indices, including…

Probability · Mathematics 2026-04-14 Zhen Hong Yu , Yu Miao

Given two orthornormal bases A and B, the basic form of the entropic uncertainty principle is stated in terms of the sum of the Shannon entropies of the probabilities of measuring A and B onto a given quantum state. State independent lower…

Quantum Physics · Physics 2020-10-28 Paolo Giorda

Under correlation-type conditions, we derive upper bounds of order $\frac{1}{\sqrt{n}}$ for the Kolmogorov distance between the distributions of weighted sums of dependent summands and the normal law.

Probability · Mathematics 2017-09-21 Sergey Bobkov , Gennadiy Chistyakov , Friedrich Götze

For an ergodic Brownian diffusion with invariant measure $\nu$, we consider a sequence of empirical distributions ($\nu$n) n$\ge$1 associated with an approximation scheme with decreasing time step ($\gamma$n) n$\ge$1 along an adapted…

Probability · Mathematics 2018-10-09 I Honoré

In this article, we establish a $L^1$ estimate for solutions to Poisson equation with mixed boundary condition, on complete noncompact manifolds with nonnegative Ricci curvature and compact manifolds with positive Ricci curvature…

Differential Geometry · Mathematics 2022-11-11 Haiqing Cheng , Tengfei Ma , Kui Wang

We prove semi-empirical concentration inequalities for random variables which are given as possibly nonlinear functions of independent random variables. These inequalities describe concentration of random variable in terms of the…

Machine Learning · Computer Science 2020-02-04 Ilja Kuzborskij , Csaba Szepesvári

We derive explicit central moment inequalities for random variables that admit a Stein coupling, such as exchangeable pairs, size--bias couplings or local dependence, among others. The bounds are in terms of moments (not necessarily…

Probability · Mathematics 2020-07-07 A. D. Barbour , Nathan Ross , Yuting Wen

his study presents a novel technique to estimate the computational complexity of sequential decoding using the Berry-Esseen theorem. Unlike the theoretical bounds determined by the conventional central limit theorem argument, which often…

Information Theory · Computer Science 2007-08-20 Po-Ning Chen , Yunghsiang S. Han , Carlos R. P. Hartmann , Hong-Bin Wu

A nonlinear Schr\"odinger equation is derived for the dynamics of a beam of ultracold fermionic atoms traversing a Bose-Einstein condensate. The condensate phonon modes are shown to provide a nonlinear medium for the fermionic atoms. A…

Statistical Mechanics · Physics 2016-08-31 Weiping Zhang , Han Pu , Chris P. Search , Pierre Meystre , E. M. Wright

We derive a Gaussian Central Limit Theorem for the sample quantiles based on locally dependent random variables with explicit convergence rate. Our approach is based on converting the problem to a sum of indicator random variables, applying…

Probability · Mathematics 2025-03-05 Partha S. Dey , Grigory Terlov

Standard chance constrained control algorithms typically rely on the assumption that uncertainties in vehicle states obey Gaussian statistics. Highly nonlinear systems tend to disrupt Gaussianity, challenging standard chance-constrained…

Optimization and Control · Mathematics 2026-04-07 Ethan Burnett , Spencer Boone

We consider solutions of stochastic differential equations which diverge to infinity as the time parameter goes to infinity. If the coefficients converge as the spacial variable goes to infinity, then the solutions will get close to some…

Probability · Mathematics 2024-11-14 Seiichiro Kusuoka , Yuichi Shiozawa

We point out necessary and sufficient conditions of uniform consistency of nonparametric sets of alternatives for widespread nonparametric tests. Nonparametric sets of alternatives can be defined both in terms of distribution function and…

Statistics Theory · Mathematics 2020-09-01 Mikhail Ermakov

This paper considers the entropy of the sum of (possibly dependent and non-identically distributed) Bernoulli random variables. Upper bounds on the error that follows from an approximation of this entropy by the entropy of a Poisson random…

Information Theory · Computer Science 2016-11-17 Igal Sason

A non perturbative renormalization scheme for Nucleon-Nucleon interaction based on boundary conditions at short distances is presented and applied to the One Pion Exchange Potential. It is free of off-shell ambiguities and ultraviolet…

Nuclear Theory · Physics 2008-11-26 M. Pavon Valderrama , E. Ruiz Arriola

Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are a critical component to empirical risk minimization. In this…

Machine Learning · Statistics 2017-02-28 Olivier Bachem , Mario Lucic , S. Hamed Hassani , Andreas Krause