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In recent years, a number of functional inequalities have been derived for Poisson random measures, with a wide range of applications. In this paper, we prove that such inequalities can be extended to the setting of marked temporal point…

Probability · Mathematics 2019-06-18 Ian Flint , Nicolas Privault , Giovanni Luca Torrisi

Quantum functional inequalities (e.g. the logarithmic Sobolev- and Poincar\'e inequalities) have found widespread application in the study of the behavior of primitive quantum Markov semigroups. The classical counterparts of these…

Quantum Physics · Physics 2017-10-11 Cambyse Rouzé , Nilanjana Datta

This paper is devoted to improvements of functional inequalities based on scalings and written in terms of relative entropies. When scales are taken into account and second moments fixed accordingly, deficit functionals provide explicit…

Analysis of PDEs · Mathematics 2015-05-25 Jean Dolbeault , Giuseppe Toscani

We study compactness and boundedness of embeddings from Sobolev type spaces on metric spaces into $L^q$ spaces with respect to another measure. The considered Sobolev spaces can be of fractional order and some statements allow also…

Functional Analysis · Mathematics 2021-08-27 Jana Björn , Agnieszka Kałamajska

Paradoxically, while the assumptions of second-order stationarity and isotropy appear outdated in light of modern spatial data, they remain remarkably robust in practice, as nonstationary methods often provide marginal improvements in…

Methodology · Statistics 2025-11-07 Federico Blasi , Reinhard Furrer

Optimal higher-order Sobolev type embeddings are shown to follow via isoperimetric inequalities. This establishes a higher-order analogue of a well-known link between first-order Sobolev embeddings and isoperimetric inequalities. Sobolev…

Functional Analysis · Mathematics 2013-11-04 Andrea Cianchi , Luboš Pick , Lenka Slavíková

We prove generalizations of the Poincare and logarithmic Sobolev inequalities corresponding to the case of fractional derivatives in measure spaces with only a minimal amount of geometric structure. The class of such spaces includes (but is…

Classical Analysis and ODEs · Mathematics 2012-05-28 Philip T. Gressman

We study generalized Poincar\'e inequalities. We prove that if a function satisfies a suitable inequality of Poincar\'e type, then the Hardy-Littlewood maximal function also obeys a meaningful estimate of similar form. As a by-product, we…

Classical Analysis and ODEs · Mathematics 2021-02-23 Olli Saari

We study the asymptotic behavior of three classes of nonlocal functionals in complete metric spaces equipped with a doubling measure and supporting a Poincar\'e inequality. We show that the limits of these nonlocal functionals are…

Functional Analysis · Mathematics 2023-10-16 Panu Lahti , Andrea Pinamonti , Xiaodan Zhou

The aim of this paper is to propose new Rosenthal-type inequalities for moments of order higher than 2 of the maximum of partial sums of stationary sequences including martingales and their generalizations. As in the recent results by…

Probability · Mathematics 2013-03-19 Florence Merlevède , Magda Peligrad

We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an…

Statistics Theory · Mathematics 2022-06-28 Alessia Caponera , Julien Fageot , Matthieu Simeoni , Victor M. Panaretos

In this paper, we consider Poincar\'e inequalities for non euclidean metrics on $\mathbb{R}^d$. These inequalities enable us to derive precise dimension free concentration inequalities for product measures. This technique is appropriate for…

Probability · Mathematics 2012-03-05 Nathael Gozlan

We study settings in which mixture and joint distributions satisfy a Poincar\'{e} (or log-Sobolev) inequality induced by a marginal and a collection of conditional distributions that are assumed to satisfy Poincar\'{e} (or log-Sobolev,…

Probability · Mathematics 2025-09-22 Vishwak Srinivasan

Iterative methods for fitting a Gaussian Random Field (GRF) model via maximum likelihood (ML) estimation requires solving a nonconvex optimization problem. The problem is aggravated for anisotropic GRFs where the number of covariance…

Machine Learning · Statistics 2021-01-12 Sam Davanloo Tajbakhsh , Necdet Serhat Aybat , Enrique Del Castillo

In the first part of this paper we prove some new Poincar\'e inequalities, with explicit constants, for domains of any hypersurface of a Riemannian manifold with sectional curvatures bounded from above. This inequalities involve the first…

Differential Geometry · Mathematics 2017-08-30 Hilário Alencar , Gregório Silva Neto

We consider square-integrable functionals of Poisson point processes for which the variance upper bound provided by the classical Poincar\'{e} inequality is suboptimal, a phenomenon known as superconcentration. In this paper, we establish a…

Probability · Mathematics 2026-03-26 Chinmoy Bhattacharjee , Rowan O'Clarey

Over the last years, minimization problems over spaces of measures have received increased interest due to their relevance in the context of inverse problems, optimal control and machine learning. A fundamental role in their numerical…

Optimization and Control · Mathematics 2024-03-19 Gerd Wachsmuth , Daniel Walter

In this paper we discuss the natural candidate for the one dimensional free Poincar\'e inequality. Two main strong points sustain this candidacy. One is the random matrix heuristic and the other the relations with the other free functional…

Operator Algebras · Mathematics 2012-04-24 Michel Ledoux , Ionel Popescu

For slowly varying fields on the scale of the lightest mass the logarithm of the vacuum functional of a massive quantum field theory can be expanded in terms of local functionals satisfying a form of the Schrodinger equation, the principal…

High Energy Physics - Theory · Physics 2009-10-30 Jiannis Pachos

We consider in this paper a class of single-ratio fractional minimization problems, in which the numerator part of the objective is the sum of a nonsmooth nonconvex function and a smooth nonconvex function while the denominator part is a…

Optimization and Control · Mathematics 2020-12-23 Na Zhang , Qia Li