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In this paper, we establish a comprehensive characterization of the generalized Lipschitz classes through the study of the rate of convergence of a family of semi-discrete sampling operators, of Durrmeyer type, in $L^p$-setting. To achieve…

Functional Analysis · Mathematics 2025-11-14 Danilo Costarelli , Michele Piconi , Gianluca Vinti

Several new inequalities for moduli of smoothness and errors of the best approximation of a function and its derivatives in the spaces $L_p$, $0<p<1$, are obtained. For example, it is shown that for any $0<p<1$ and $k,\,r\in \mathbb{N}$ one…

Classical Analysis and ODEs · Mathematics 2016-12-26 Yurii Kolomoitsev

Based on two independent samples X_1,...,X_m and X_{m+1},...,X_n drawn from multivariate distributions with unknown Lebesgue densities p and q respectively, we propose an exact multiple test in order to identify simultaneously regions of…

Statistics Theory · Mathematics 2009-08-12 Angelika Rohde

We study approximation properties of linear sampling operators in the spaces $L_p$ for $1\le p<\infty$. By means of the Steklov averages, we introduce a new measure of smoothness that simultaneously contains information on the smoothness of…

Classical Analysis and ODEs · Mathematics 2022-02-11 Yurii Kolomoitsev , Tetiana Lomako

We establish quantitative estimates for sampling (dominating) sets in model spaces associated with meromorphic inner functions, i.e. those corresponding to de Branges spaces. Our results encompass the Logvinenko-Sereda-Panejah (LSP) Theorem…

Complex Variables · Mathematics 2017-07-26 Andreas Hartmann , Philippe Jaming , Karim Kellay

We consider the problem of estimating probability density functions based on sample data, using a finite mixture of densities from some component class. To this end, we introduce the $h$-lifted Kullback--Leibler (KL) divergence as a…

Machine Learning · Statistics 2024-12-24 Mark Chiu Chong , Hien Duy Nguyen , TrungTin Nguyen

We investigate two density questions for Sobolev, Besov and Triebel--Lizorkin spaces on rough sets. Our main results, stated in the simplest Sobolev space setting, are that: (i) for an open set $\Omega\subset\mathbb R^n$,…

Functional Analysis · Mathematics 2022-08-29 António Caetano , David P. Hewett , Andrea Moiola

The problem of constructing confidence sets that are adaptive in L^2-loss over a continuous scale of Sobolev classes of probability densities is considered. Adaptation holds, where possible, with respect to both the radius of the Sobolev…

Statistics Theory · Mathematics 2013-12-23 Adam D. Bull , Richard Nickl

We unify and extend the semigroup and the PDE approaches to stochastic maximal regularity of time-dependent semilinear parabolic problems with noise given by a cylindrical Brownian motion. We treat random coefficients that are only…

Analysis of PDEs · Mathematics 2019-02-12 Pierre Portal , Mark Veraar

We consider the problem of learning an $\varepsilon$-optimal policy in a general class of continuous-space Markov decision processes (MDPs) having smooth Bellman operators. Given access to a generative model, we achieve rate-optimal sample…

Machine Learning · Computer Science 2024-05-13 Davide Maran , Alberto Maria Metelli , Matteo Papini , Marcello Restelli

This paper constructs unique compactly supported functions in Sobolev spaces that have minimal norm, maximal support, and maximal central value, under certain renormalizations. They may serve as optimized basis functions in interpolation or…

Numerical Analysis · Mathematics 2024-09-04 Robert Schaback

The sample paths of white noise are proved to be elements of certain Besov spaces with dominating mixed smoothness. Unlike in isotropic spaces, here the regularity does not get worse with increasing space dimension. Consequently, white…

Probability · Mathematics 2020-05-25 Felix Hummel

We prove the weighted $L^p$ regularity of the ordinary Bergman and Cauchy-Szeg\H{o} projections on strongly pseudoconvex domains $D$ in $\mathbb{C}^n$ with near minimal smoothness for appropriate generalizations of the $B_p/A_p$ classes. In…

Complex Variables · Mathematics 2023-10-18 Nathan A. Wagner , Brett D. Wick

Optimal lower bounds for discrepancy in Besov spaces with dominating mixed smoothness are known from the work of Triebel. Hinrichs proved upper bounds in the plane. In this work we systematically analyse the problem, starting with a survey…

Numerical Analysis · Mathematics 2014-02-19 Lev Markhasin

We consider the problem of minimax estimation of the entropy of a density over Lipschitz balls. Dropping the usual assumption that the density is bounded away from zero, we obtain the minimax rates $(n\ln n)^{-s/(s+d)} + n^{-1/2}$ for…

Statistics Theory · Mathematics 2019-11-12 Yanjun Han , Jiantao Jiao , Tsachy Weissman , Yihong Wu

Mixture of experts (MoE) models are widely applied for conditional probability density estimation problems. We demonstrate the richness of the class of MoE models by proving denseness results in Lebesgue spaces, when inputs and outputs…

Statistics Theory · Mathematics 2021-10-12 Hien Duy Nguyen , TrungTin Nguyen , Faicel Chamroukhi , Geoffrey McLachlan

We prove density of smooth functions in subspaces of Sobolev- and higher order $BV$-spaces of kind $W^{m,p}(\Omega)\cap L^q(\Omega-D)$ and $BV^m(\Omega)\cap L^q(\Omega-D)$, respectively, where $\Omega\subset\mathbb{R}^n$ ($n\in\mathbb{N}$)…

Analysis of PDEs · Mathematics 2018-03-28 Jan Mueller

This paper studies smoothing properties of the local fractional maximal operator, which is defined in a proper subdomain of the Euclidean space. We prove new pointwise estimates for the weak gradient of the maximal function, which imply…

Functional Analysis · Mathematics 2015-06-17 Toni Heikkinen , Juha Kinnunen , Janne Korvenpää , Heli Tuominen

We consider regularity properties of stochastic kinetic equations with multiplicative noise and drift term which belongs to a space of mixed regularity ($L^p$-regularity in the velocity-variable and Sobolev regularity in the…

Probability · Mathematics 2017-05-16 Ennio Fedrizzi , Franco Flandoli , Enrico Priola , Julien Vovelle

We study an approximation method for partially observed Markov decision processes (POMDPs) with continuous spaces. Belief MDP reduction, which has been the standard approach to study POMDPs requires rigorous approximation methods for…

Optimization and Control · Mathematics 2025-01-20 Ali Devran Kara , Erhan Bayraktar , Serdar Yuksel
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