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SHAP (SHapley Additive exPlanations) has become a popular method to attribute the prediction of a machine learning model on an input to its features. One main challenge of SHAP is the computation time. An exact computation of Shapley values…

Machine Learning · Statistics 2023-09-06 Linwei Hu , Ke Wang

Statistical Shape Modeling (SSM) is a quantitative method for analyzing morphological variations in anatomical structures. These analyses often necessitate building models on targeted anatomical regions of interest to focus on specific…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Hong Xu , Alan Morris , Shireen Y. Elhabian

In this survey, we use (more or less) elementary means to establish the well-known result that for any given smooth multivariate function, the respective multivariate Bernstein polynomials converge to that function in all derivatives on…

Classical Analysis and ODEs · Mathematics 2016-09-08 Adrian Fellhauer

We derive a three-term recurrence relation for computing the polynomial of best approximation in the uniform norm to $x^{-1}$ on a finite interval with positive endpoints. As application, we consider two-level methods for scalar elliptic…

Numerical Analysis · Mathematics 2012-05-24 Johannes K. Kraus , Panayot S. Vassilevski , Ludmil T. Zikatanov

We provide a comprehensive study of interrelations between different measures of smoothness of functions on various domains and smoothness properties of approximation processes. Two general approaches to this problem have been developed:…

Classical Analysis and ODEs · Mathematics 2020-03-18 Yu. Kolomoitsev , S. Tikhonov

We consider the problem of approximating an analytic function on a compact interval from its values at $M+1$ distinct points. When the points are equispaced, a recent result (the so-called impossibility theorem) has shown that the best…

Numerical Analysis · Mathematics 2018-04-09 Ben Adcock , Rodrigo Platte , Alexei Shadrin

This paper makes the following original contributions. First, we develop a unifying framework for testing shape restrictions based on the Wald principle. The test has asymptotic uniform size control and is uniformly consistent. Second, we…

Econometrics · Economics 2021-08-03 Zheng Fang

The Bernstein approximation problem is to determine whether or not the space of all polynomials is dense in a given weighted $C_0$-space on the real line. A theorem of L. de Branges characterizes non--density by existence of an entire…

Complex Variables · Mathematics 2012-07-24 Anton Baranov , Harald Woracek

Some properties of generalized convexity for sets and for functions are identified in case of the reliability polynomials of two dual minimal networks. A method of approximating the reliability polynomials of two dual minimal network is…

Discrete Mathematics · Computer Science 2021-12-14 Gabriela Cristescu , Vlad-Florin Dragoi , Sorin-Horatiu Hoara

We prove invariance theorems for general inequalities of different metrics and apply them to limit relations between the sharp constants in the multivariate Markov-Bernstein-Nikolskii type inequalities with the polyharmonic operator for…

Classical Analysis and ODEs · Mathematics 2020-02-27 Michael I. Ganzburg

We develop the theory of invariant structure preserving and free functions on a general structured topological space. We show that an invariant structure preserving function is pointwise approximiable by the appropriate analog of…

Functional Analysis · Mathematics 2021-04-07 J. E. Pascoe

Let $\Lambda$ be a uniformly discrete set and $S$ be a compact set in $R$. We prove that if there exists a bounded sequence of functions in Paley--Wiener space $PW_S$, which approximates $\delta-$functions on $\Lambda$ with $l^2-$error $d$,…

Classical Analysis and ODEs · Mathematics 2013-04-03 Alexander Olevskii , Alexander Ulanovskii

Approximating a function with a finite series, e.g., involving polynomials or trigonometric functions, is a critical tool in computing and data analysis. The construction of such approximations via now-standard approaches like least squares…

Optimization and Control · Mathematics 2021-08-30 Dihan Dai , Yekaterina Epshteyn , Akil Narayan

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

The family of Weisfeiler-Leman equivalences on graphs is a widely studied approximation of graph isomorphism with many different characterizations. We study these, and other approximations of isomorphism defined in terms of refinement…

Combinatorics · Mathematics 2020-10-21 Anuj Dawar , Danny Vagnozzi

Polynomial approximations to boolean functions have led to many positive results in computer science. In particular, polynomial approximations to the sign function underly algorithms for agnostically learning halfspaces, as well as…

Computational Complexity · Computer Science 2014-12-09 Mark Bun , Thomas Steinke

We study the numerical approximation of the invariant measure of a viscous scalar conservation law, one-dimensional and periodic in the space variable, and stochastically forced with a white-in-time but spatially correlated noise. The flux…

Analysis of PDEs · Mathematics 2021-05-27 Sébastien Boyaval , Sofiane Martel , Julien Reygner

The number of lattice points $\left| tP \cap \mathbb{Z}^d \right|$, as a function of the real variable $t>1$ is studied, where $P \subset \mathbb{R}^d$ belongs to a special class of algebraic cross-polytopes and simplices. It is shown that…

Number Theory · Mathematics 2018-06-05 Bence Borda

We prove matching direct and inverse theorems for (algebraic) polynomial approximation with doubling weights $w$ having finitely many zeros and singularities (i.e., points where $w$ becomes infinite) on an interval and not too ``rapidly…

Classical Analysis and ODEs · Mathematics 2015-07-20 Kirill A. Kopotun

In this paper, we study the Jacobi frame approximation with equispaced samples and derive an error estimation. We observe numerically that the approximation accuracy gradually decreases as the extended domain parameter $\gamma$ increases in…

Numerical Analysis · Mathematics 2022-02-23 Xianru Chen