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We study uniqueness of best approximation in Orlicz spaces L$\Phi$, for different types of convex functions $\Phi$ and for some finite dimensional approximation classes of functions, where Tchebycheff spaces, and more general approximation…

Functional Analysis · Mathematics 2024-06-17 Ana Benavente , Juan Costa Ponce , Sergio Favier

We obtain new sampling discretization results in Orlicz norms on finite dimensional spaces. As applications, we study sampling recovery problems, where the error of the recovery process is calculated with respect to different Orlicz norms.…

Functional Analysis · Mathematics 2024-08-27 Egor Kosov , Sergey Tikhonov

The boundedness (continuity) of composition operators from some function space to another one is significant, though there are few results about this problem. Thus, in this study, we provide necessary and sufficient conditions on the…

Functional Analysis · Mathematics 2024-09-18 Naoya Hatano , Masahiro Ikeda , Ryota Kawasumi

The aim of this paper is investigating of Orlicz spaces with exponential function and correspondence Orlicz norm: we introduce some new equivalent norms, obtain the tail characterization, study the product of functions in Orlicz spaces etc.…

Functional Analysis · Mathematics 2007-05-23 Eugene Ostrovsky

This paper studies the probabilistic function approximation problem over reproducing kernel Hilbert spaces. We show the existence and uniqueness of the optimizer under mild assumptions. Furthermore, we generalize the celebrated representer…

Functional Analysis · Mathematics 2025-07-16 Dongwei Chen , Kai-Hsiang Wang

An extension of Marcinkiewicz Interpolation Theorem, allowing intermediate spaces of Orlicz type, is proved. This generalization yields a necessary and sufficient condition so that every quasilinear operator, which maps the set, $S(X,\mu)$,…

Classical Analysis and ODEs · Mathematics 2017-11-28 Ron Kerman , Rama Rawat , Rajesh K. Singh

The sparse polynomial approximation of continuous functions has emerged as a prominent area of interest in function approximation theory in recent years. A key challenge within this domain is the accurate estimation of approximation errors.…

Numerical Analysis · Mathematics 2025-06-10 Renzhong Feng , Bowen Zhang

We consider a class of operator-induced norms, acting as finite-dimensional surrogates to the L2 norm, and study their approximation properties over Hilbert subspaces of L2 . The class includes, as a special case, the usual empirical norm…

Statistics Theory · Mathematics 2011-06-01 Arash A. Amini , Martin J. Wainwright

This paper surveys recent developments in the sampling discretization of integral and uniform norms for functions in general finite-dimensional spaces. These results generalize the classical Marcinkiewicz-Zygmund inequalities for…

Numerical Analysis · Mathematics 2026-03-04 F. Dai , E. Kosov , V. Temlyakov

We derive in this preprint the exact up to multiplicative constant non-asymptotical estimates for the norms of some non-linear in general case operators, for example, the so-called maximal functional operators, in two probabilistic…

Functional Analysis · Mathematics 2017-06-26 E. Ostrovsky , L. Sirota

In this paper, we present some applications of the multivariate sampling Kantorovich operators $S_w$ to seismic engineering. The mathematical theory of these operators, both in the space of continuous functions and in Orlicz spaces, show…

Computer Vision and Pattern Recognition · Computer Science 2014-11-12 Danilo Costarelli , Federico Cluni , Anna Maria Minotti , Gianluca Vinti

We consider approximation by functions with finite support and characterize its approximation spaces in terms of interpolation spaces and Lorentz spaces.

Classical Analysis and ODEs · Mathematics 2017-07-05 Bo Ling , Yongping Liu

This paper studies the problem of approximating a function $f$ in a Banach space $X$ from measurements $l_j(f)$, $j=1,\dots,m$, where the $l_j$ are linear functionals from $X^*$. Most results study this problem for classical Banach spaces…

Numerical Analysis · Mathematics 2016-08-08 Ronald DeVore , Guergana Petrova , Przemyslaw Wojtaszczyk

multiplication operator on a Hilbert space may be approximated with finite sections by choosing an orthonormal basis of the Hilbert space. Nonzero multiplication operators on $L^2$ spaces of functions are never compact and then such…

Numerical Analysis · Mathematics 2007-05-23 Stefano Serra Capizzano

The maximal Orlicz space such that the mixed logarithmic means of multiple Fourier series for the functions from this space converge in $L_{1}$-norm is found.

Analysis of PDEs · Mathematics 2013-10-31 Ushangi Goginava , Larry Gogoladze

In this paper, we establish sharp bounds for a family of Kantorovich-type neural network operators within the general frameworks of Sobolev-Orlicz and Orlicz spaces. We establish both strong (in terms of the Luxemburg norm) and weak (in…

Functional Analysis · Mathematics 2026-01-09 Danilo Costarelli , Michele Piconi

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

We introduce a novel concept of convergence for Markovian processes within Orlicz spaces, extending beyond the conventional approach associated with $L_p$ spaces. After showing that Markovian operators are contractive in Orlicz spaces, our…

Information Theory · Computer Science 2025-11-24 Amedeo Roberto Esposito , Marco Mondelli

Let $L$ be a homogeneous divergence form higher order elliptic operator with complex bounded measurable coefficients on $\mathbb{R}^n$ and $X$ a ball quasi-Banach function space on $\mathbb{R}^n$ satisfying some mild assumptions. Denote by…

Functional Analysis · Mathematics 2022-07-11 Xiaosheng Lin , Dachun Yang , Sibei Yang , Wen Yuan

Operator learning has been highly successful for continuous mappings between infinite-dimensional spaces, such as PDE solution operators. However, many operators of interest-including differential operators-are discontinuous or set-valued,…

Machine Learning · Computer Science 2026-05-13 Takashi Furuya , Yury Korolev , Takaharu Yaguchi