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Given three transversal and sufficiently regular hypersurfaces in R^3 it follows from work of Bennett-Carbery-Wright that the convolution of two L^2 functions supported of the first and second hypersurface, respectively, can be restricted…

Analysis of PDEs · Mathematics 2013-12-12 Ioan Bejenaru , Sebastian Herr , Daniel Tataru

Modern statistical applications often involve minimizing an objective function that may be nonsmooth and/or nonconvex. This paper focuses on a broad Bregman-surrogate algorithm framework including the local linear approximation, mirror…

Optimization and Control · Mathematics 2021-12-20 Yiyuan She , Zhifeng Wang , Jiuwu Jin

We propose a convex-optimization-based framework for computation of invariant measures of polynomial dynamical systems and Markov processes, in discrete and continuous time. The set of all invariant measures is characterized as the feasible…

Optimization and Control · Mathematics 2020-09-18 Milan Korda , Didier Henrion , Igor Mezic

We obtain the classical Hanner inequalities by the Bellman function method. These inequalities give sharp estimates for the moduli of convexity of Lebesgue spaces. Easy ideas from differential geometry help us to find the Bellman function…

Classical Analysis and ODEs · Mathematics 2016-04-07 Paata Ivanisvili , Dmitriy M. Stolyarov , Pavel B. Zatitskiy

We consider $L^2$-approximation on weighted reproducing kernel Hilbert spaces of functions depending on infinitely many variables. We focus on unrestricted linear information, admitting evaluations of arbitrary continuous linear…

Numerical Analysis · Mathematics 2026-01-13 Kumar Harsha , Michael Gnewuch , Marcin Wnuk

We present an optimization algorithm that can identify a global minimum of a potentially nonconvex smooth function with high probability, assuming the Gibbs measure of the potential satisfies a logarithmic Sobolev inequality. Our…

Optimization and Control · Mathematics 2025-09-16 Daniel Cortild , Claire Delplancke , Nadia Oudjane , Juan Peypouquet

This paper is the second part of our series of works to establish $L^2$ estimates and existence theorems for the $\overline{\partial}$ operators in infinite dimensions. In this part, we consider the most difficult case, i.e., the underlying…

Functional Analysis · Mathematics 2024-05-24 Zhouzhe Wang , Jiayang Yu , Xu Zhang

In the present work we give a simple method to obtain weighted norm inequalities in Lebesgue spaces $L_{p,\gamma }$ with Muckenhoupt weights $\gamma $. This method is different from celebrated Extrapolation or Interpolation Theory. In this…

Classical Analysis and ODEs · Mathematics 2021-09-06 Ramazan Akgün

In the context of variable exponent Lebesgue spaces equipped with a lower Ahlfors measure we obtain weighted norm inequalities over bounded domains for the centered fractional maximal function and the fractional integral operator.

Analysis of PDEs · Mathematics 2009-07-31 Osvaldo Gorosito , Gladis Pradolini , Oscar Salinas

We derive an extension of the Walnut-Daubechies criterion for the invertibility of frame operators. The criterion concerns general reproducing systems and Besov-type spaces. As an application, we conclude that $L^2$ frame expansions…

Functional Analysis · Mathematics 2022-05-04 José Luis Romero , Jordy Timo van Velthoven , Felix Voigtlaender

In this paper we derive martingale estimating functions for the dimensionality parameter of a Bessel process based on the eigenfunctions of the diffusion operator. Since a Bessel process is non-ergodic and the theory of martingale…

Probability · Mathematics 2020-07-27 Nicole Hufnagel , Jeannette H. C. Woerner

In this work we study boundedness of Littlewood-Paley-Stein square func- tions associated to multilinear operators. We prove weighted Lebesgue space bounds for square functions under relaxed regularity and cancellation conditions that are…

Functional Analysis · Mathematics 2013-06-04 Lucas Chaffee , Jarod Hart , Lucas Oliveira

We investigate the structure of norm-preserving and linear but not necessarily surjective operators on variable-exponent, discrete Lebesgue spaces. A certain class of isometries, novel to this work, are especially considered; this class…

Functional Analysis · Mathematics 2020-07-13 Philip M. Gipson

In this work, a pre-Gr\"{u}ss inequality for positive Hilbert space operators is proved. So that, some numerical radius inequalities are proved. On the other hand, based on a non-commutative Binomial formula, a non-commutative upper bound…

Functional Analysis · Mathematics 2018-11-21 Mohammad W. Alomari

We establish sharp large-deviation asymptotic estimates for the maximum order statistic of i.i.d.\ standard normal random variables on all Borel subsets of the positive real line. This result yields more accurate tail approximations than…

Probability · Mathematics 2025-12-23 José M. Zapata

In this paper, motivated by perturbation theory of operators, we present some upper bounds for $|||f(A)Xg(B)+ X|||$ in terms of $|||\,|AXB|+|X|\,|||$ and $|||f(A)Xg(B)- X|||$ in terms of $|||\,|AX|+|XB|\,|||$, where $A, B$ are $G_{1}$…

Functional Analysis · Mathematics 2017-09-26 Fuad Kittaneh , Mohammad Sal Moslehian , Mohammad Sababheh

We obtain estimates in Besov, Lizorkin-Triebel and Lorentz spaces of differential forms on R^n in terms of their L^1 norm.

Analysis of PDEs · Mathematics 2009-12-22 Jean Van Schaftingen

In this paper, we introduce a quadratic stochastic operators on the set of all probability measures of a measurable space. We study the dynamics of the Lebesgue quadratic stochastic operator on the set of all Lebesgue measures of the set…

Dynamical Systems · Mathematics 2016-01-11 Nasir Ganikhodjaev , Mansoor Saburov , Ramazon Muhitdinov

We revisit the properties of Bessel-Riesz operators and refine the proof of the boundedness of these operators on generalized Morrey spaces using Young's inequality. We also obtain an estimate for the norm of these operators on generalized…

Analysis of PDEs · Mathematics 2018-02-20 Mochammad Idris , Hendra Gunawan , Eridani

The paper proposes a method for constructing a sparse estimator for the inverse covariance (concentration) matrix in high-dimensional settings. The estimator uses a penalized normal likelihood approach and forces sparsity by using a…

Statistics Theory · Mathematics 2008-06-26 Adam J. Rothman , Peter J. Bickel , Elizaveta Levina , Ji Zhu