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Suppose that $\ff \in \reals^{n}$ is a vector of $n$ error-contaminated measurements of $n$ smooth values measured at distinct and strictly ascending abscissae. The following projective technique is proposed for obtaining a vector of smooth…

Numerical Analysis · Computer Science 2010-07-27 M. P. Cullinan

New bounds for the $k$-th order derivatives of the solutions of the normal and multivariate normal Stein equations are obtained. Our general order bounds involve fewer derivatives of the test function than those in the existing literature.…

Probability · Mathematics 2017-03-21 Robert E. Gaunt

We prove infinite-dimensional second order Poincar\'e inequalities on Wiener space, thus closing a circle of ideas linking limit theorems for functionals of Gaussian fields, Stein's method and Malliavin calculus. We provide two…

Probability · Mathematics 2010-02-12 Ivan Nourdin , Giovanni Peccati , Gesine Reinert

This article compares the distributions of integer-valued random variables and Poisson random variables. It considers the total variation and the Wasserstein distance and provides, in particular, explicit bounds on the pointwise difference…

Probability · Mathematics 2021-04-07 Federico Pianoforte , Matthias Schulte

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

Poincar{\'e} inequalities are ubiquitous in probability and analysis and have various applications in statistics (concentration of measure, rate of convergence of Markov chains). The Poincar{\'e} constant, for which the inequality is tight,…

Probability · Mathematics 2019-11-25 Loucas Pillaud-Vivien , Francis Bach , Tony Lelièvre , Alessandro Rudi , Gabriel Stoltz

In this paper, we first consider the graph of $(F_1,F_{2},\cdots,F_{n})$ on $\overline{\mathbb{D}}^{n},$ where $F_{j}(z)=\bar{z}^{m_{j}}_{j}+R_{j}(z),j=1,2,\cdots,n,$ which has non-isolated CR-singularities if $m_{j}>1$ for some…

Complex Variables · Mathematics 2022-10-14 Golam Mostafa Mondal

Non-uniform estimates are obtained for Poisson, compound Poisson, translated Poisson, negative binomial and binomial approximations to sums of of m-dependent integer-valued random variables. Estimates for Wasserstein metric also follow…

Probability · Mathematics 2014-08-19 P. Vellaisamy , V. Cekanavicius

In this paper, we obtain new bounds for the inequalities of Simpson and Hermite-Hadamard type for functions whose second derivatives absolute values are P-convex. These bounds can be much better than some obtained bounds. Some applications…

Classical Analysis and ODEs · Mathematics 2011-03-11 M. E. Ozdemir , Cetin Yildiz

It is shown that the new formula for the field theory Poisson brackets arise naturally in the extension of the formal variational calculus incorporating divergences. The linear spaces of local functionals, evolutionary vector fields,…

Differential Geometry · Mathematics 2007-05-23 Vladimir O. Soloviev

Distance correlation is a novel class of multivariate dependence measure, taking positive values between 0 and 1, and applicable to random vectors of arbitrary dimensions, not necessarily equal. It offers several advantages over the…

Computation · Statistics 2024-05-06 Blanca E. Monroy-Castillo , M. A , Jácome , Ricardo Cao

The families of $f$-divergences (e.g. the Kullback-Leibler divergence) and Integral Probability Metrics (e.g. total variation distance or maximum mean discrepancies) are widely used to quantify the similarity between probability…

Statistics Theory · Mathematics 2021-06-08 Rohit Agrawal , Thibaut Horel

When the nonconvex problem is complicated by stochasticity, the sample complexity of stochastic first-order methods may depend linearly on the problem dimension, which is undesirable for large-scale problems. In this work, we propose…

Optimization and Control · Mathematics 2024-10-01 Yue Xie , Jiawen Bi , Hongcheng Liu

In this paper, we propose the Fourier Discrepancy Function, a new discrepancy to compare discrete probability measures. We show that this discrepancy takes into account the geometry of the underlying space. We prove that the Fourier…

Machine Learning · Statistics 2021-11-19 Auricchio Gennaro , Codegoni Andrea , Gualandi Stefano , Zambon Lorenzo

The optimization problem concerning the determination of the minimizer for the sum of convex functions holds significant importance in the realm of distributed and decentralized optimization. In scenarios where full knowledge of the…

Optimization and Control · Mathematics 2024-09-24 Kananart Kuwaranancharoen , Shreyas Sundaram

Variational convexity, together with ist strong counterpart, of extended-real-valued functions has been recently introduced by Rockafellar. In this paper we present second-order characterizations of these properties, i.e., conditions using…

Optimization and Control · Mathematics 2025-02-04 Helmut Gfrerer

Solutions to many important partial differential equations satisfy bounds constraints, but approximations computed by finite element or finite difference methods typically fail to respect the same conditions. Chang and Nakshatrala enforce…

Numerical Analysis · Mathematics 2024-03-14 Robert C. Kirby , Daniel Shapero

Given two sets $x_1^{(1)},\ldots,x_{n_1}^{(1)}$ and $x_1^{(2)},\ldots,x_{n_2}^{(2)}\in\mathbb{R}^p$ (or $\mathbb{C}^p$) of random vectors with zero mean and positive definite covariance matrices $C_1$ and $C_2\in\mathbb{R}^{p\times p}$ (or…

Probability · Mathematics 2018-10-11 Romain Couillet , Malik Tiomoko , Steeve Zozor , Eric Moisan

In this paper, we study two specific types of $d$-dimensional Poisson functionals: a double-sum type and a sum-log-sum type, both over pairs of Poisson points. On these functionals, we impose column-type dependence, i.e., local behavior in…

Probability · Mathematics 2025-12-24 Hanna Döring , Adélie Garin , Christian Hirsch , Nikolaj Nyvold Lundbye

We prove concentration inequalities for general functions of weakly dependent random variables satisfying the Dobrushin condition. In particular, we show Talagrand's convex distance inequality for this type of dependence. We apply our…

Probability · Mathematics 2014-09-02 Daniel Paulin
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