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Submodular functions are a fundamental object of study in combinatorial optimization, economics, machine learning, etc. and exhibit a rich combinatorial structure. Many subclasses of submodular functions have also been well studied and…

Data Structures and Algorithms · Computer Science 2013-04-19 Nikhil R. Devanur , Shaddin Dughmi , Roy Schwartz , Ankit Sharma , Mohit Singh

In this work we produce a framework for constructing universal function approximators on graph isomorphism classes. We prove how this framework comes with a collection of theoretically desirable properties and enables novel analysis. We…

Data Structures and Algorithms · Computer Science 2020-10-27 Rickard Brüel-Gabrielsson

Let $U\subseteq\mathbb{R}^{n}$ be open and convex. We show that every (not necessarily Lipschitz or strongly) convex function $f:U\to\mathbb{R}$ can be approximated by real analytic convex functions, uniformly on all of $U$. In doing so we…

Functional Analysis · Mathematics 2012-01-17 D. Azagra

We apply the technique of self-similar exponential approximants based on successive truncations of continued exponentials to reconstruct functional laws of the quasi-exponential class from the knowledge of only a few terms of their power…

Condensed Matter · Physics 2009-11-07 S. Gluzman , D. Sornette , V. I. Yukalov

We introduce an asymmetric operator of generalised translation, define the generalised modulus of smoothness by its means, and obtain the direct and inverse theorems in approximation theory for it.

Functional Analysis · Mathematics 2012-08-31 Mikhail K. Potapov , Faton M. Berisha

We prove the existence of entire functions that achieve universal approximations on certain countable sequences of translation operators .

Functional Analysis · Mathematics 2022-02-22 Nikos Tsirivas

Given a finite number of samples of a continuous set-valued function F, mapping an interval to non-empty compact subsets of $\mathbb{R}^d$, $F: [a,b] \to K(\mathbb{R}^d)$, we discuss the problem of computing good approximations of F. We…

Numerical Analysis · Mathematics 2025-01-27 Nira Dyn , David Levin

In this article we propose building general-purpose function approximators on top of Haar Scattering Networks. We advocate that this architecture enables a better comprehension of feature extraction, in addition to its implementation…

Machine Learning · Statistics 2018-04-11 Fernando Fernandes Neto

This paper studies the approximation of generalized ridge functions, namely of functions which are constant along some submanifolds of $\mathbb{R}^N$. We introduce the notion of linear-sleeve functions, whose function values only depend on…

Numerical Analysis · Mathematics 2017-01-26 Sandra Keiper

We investigate the rational approximation of fractional powers of unbounded positive operators attainable with a specific integral representation of the operator function. We provide accurate error bounds by exploiting classical results in…

Numerical Analysis · Mathematics 2024-03-19 Lidia Aceto , Paolo Novati

In some applications, one is interested in reconstructing a function $f$ from its Fourier series coefficients. The problem is that the Fourier series is slowly convergent if the function is non-periodic, or is non-smooth. In this paper, we…

Numerical Analysis · Mathematics 2020-04-14 David Levin

We develop a general, functional calculus approach to approximation of $C_0$-semigroups on Banach spaces by bounded completely monotone functions of their generators. The approach comprises most of well-known approximation formulas, yields…

Functional Analysis · Mathematics 2018-07-10 A. Gomilko , S. Kosowicz , Yu. Tomilov

One of the basic principles of Approximation Theory is that the quality of approximations increase with the smoothness of the function to be approximated. Functions that are smooth in certain subdomains will have good approximations in…

Numerical Analysis · Mathematics 2016-12-23 Licia Lenarduzzi , Robert Schaback

This paper concerns the universal approximation property with neural networks in variable Lebesgue spaces. We show that, whenever the exponent function of the space is bounded, every function can be approximated with shallow neural networks…

Functional Analysis · Mathematics 2020-07-09 Ángela Capel , Jesús Ocáriz

We consider approximations of a continuous function on a countable normed Fr\'{e}chet space by analytic and $*$-analytic. Also we found a criterium of the existence of an extension of a continuous function from a dense subspace of a…

Functional Analysis · Mathematics 2015-05-01 M. A. Mytrofanov , A. V. Ravsky

In the present paper, we use a generalised shift operator in order to define a generalised modulus of smoothness. By its means, we define generalised Lipschitz classes of functions, and we give their constructive characteristics.…

Functional Analysis · Mathematics 2014-01-28 Faton M. Berisha , Nimete Sh. Berisha

It is well known that rational approximation theory involves degenerate hypergeometric functions and, in particular, the Pad\'e approximation of the exponential function is closely related to Kummer hypergeometric functions. Recently, in…

Optimization and Control · Mathematics 2022-12-06 Islam Boussaada , Guilherme Mazanti , Silviu-Iulian Niculescu

We prove the existence of holomorphic functions $f$ defined on any open convex subset ${\rm \Omega}\subset {{\mathbb C}}^n$, whose partial sums of the Taylor developments approximate uniformly any complex polynomial on any convex compact…

Complex Variables · Mathematics 2013-02-19 Nicholas J. Daras , Vassili Nestoridis

The stability and approximation properties of transfer functions of generalized Bessel polynomials (GBP) are investigated. Sufficient conditions are established for the GBP to be Hurwitz. It is shown that the Pad\'e approximants of $e^{-s}$…

Classical Analysis and ODEs · Mathematics 2016-11-17 Jose R. Martinez

We define a free holomorphic function to be a function that is locally a bounded nc-function. We prove that free holomorphic functions are the functions that are locally uniformly approximable by free polynomials. We prove a realization…

Operator Algebras · Mathematics 2013-07-03 Jim Agler , John E. McCarthy