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A theorem is proved concerning approximation of analytic functions by multivariate polynomials in the $s$-dimensional hypercube. The geometric convergence rate is determined not by the usual notion of degree of a multivariate polynomial,…

Numerical Analysis · Mathematics 2016-08-09 Lloyd N. Trefethen

Massive classification, a classification task defined over a vast number of classes (hundreds of thousands or even millions), has become an essential part of many real-world systems, such as face recognition. Existing methods, including the…

Computer Vision and Pattern Recognition · Computer Science 2018-01-08 Xingcheng Zhang , Lei Yang , Junjie Yan , Dahua Lin

Mathematical models are essential for understanding and making predictions about systems arising in nature and engineering. Yet, mathematical models are a simplification of true phenomena, thus making predictions subject to uncertainty.…

Numerical Analysis · Mathematics 2023-03-03 Mark Hobbs , Hussein Rappel , Tim Dodwell

The shape of homogeneous, generic, smooth convex bodies as described by the Euclidean distance with nondegenerate critical points, measured from the center of mass represents a rather restricted class M_C of Morse-Smale functions on S^2.…

Differential Geometry · Mathematics 2015-12-01 Gábor Domokos , Zsolt Lángi , Tí mea Szabó

A map between manifolds induces stratifications of both the source and the target according to the occurring multisingularities. In this paper, we study universal expressions-called higher Thom polynomials-that describe the…

Algebraic Geometry · Mathematics 2025-10-28 Jakub Koncki , Richárd Rimányi

Relations between components of the effective tensors of composites that hold regardless of composite's microstructure are called exact relations. Relations between components of the effective tensors of all laminates are called lamination…

Rings and Algebras · Mathematics 2013-09-19 Yury Grabovsky

Let $G$ be a group with a metric $\mathrm{d}$ invariant under left and right translations, and let $\bar{\mathbb{D}}_r$ be the ball of radius $r$ around the identity. A $(k,r)$-metric approximate subgroup is a symmetric subset $X$ of $G$…

Group Theory · Mathematics 2025-10-01 E. Hrushovski , A. Rodriguez Fanlo

The purpose of this article is to produce effective versions of some rigidity results in algebra and geometry. On the geometric side, we focus on the spectrum of primitive geodesic lengths (resp., complex lengths) for arithmetic hyperbolic…

Geometric Topology · Mathematics 2018-11-21 Benjamin Linowitz , D. B. McReynolds , Paul Pollack , Lola Thompson

We define fully exact module categories, a subclass of exact module categories over a finite braided tensor category that is stable under the relative Deligne product. In contrast, we demonstrate with examples in both zero and non-zero…

Quantum Algebra · Mathematics 2026-01-30 Azat M. Gainutdinov , Robert Laugwitz

The classical theory of elliptic curves with complex multiplication is a fundamental tool for studying the arithmetic of abelian extensions of imaginary quadratic fields. While no direct analogue is available for real quadratic fields, a…

Number Theory · Mathematics 2023-09-22 Paulina Fust , Judith Ludwig , Alice Pozzi , Mafalda Santos , Hanneke Wiersema

Machine learning models provide statistically impressive results which might be individually unreliable. To provide reliability, we propose an Epistemic Classifier (EC) that can provide justification of its belief using support from the…

Machine Learning · Computer Science 2020-10-20 Chitresh Bhushan , Zhaoyuan Yang , Nurali Virani , Naresh Iyer

This paper investigates a new property of formal languages called REG-measurability where REG is the class of regular languages. Intuitively, a language \(L\) is REG-measurable if there exists an infinite sequence of regular languages that…

Formal Languages and Automata Theory · Computer Science 2020-11-18 Ryoma Sin'ya

While classical data analysis has addressed observations that are real numbers or elements of a real vector space, at present many statistical problems of high interest in the sciences address the analysis of data that consist of more…

Statistics Theory · Mathematics 2023-08-15 Zhigang Yao , Jiaji Su , Bingjie Li , Shing-Tung Yau

Despite spectacular advances in defining invariants for simply connected smooth and symplectic 4-dimensional manifolds and the discovery of effective surgical techniques, we still have been unable to classify simply connected smooth…

Geometric Topology · Mathematics 2007-05-23 Ronald Fintushel , Ronald J. Stern

We introduce the notion of large scale inductive dimension for asymptotic resemblance spaces. We prove that the large scale inductive dimension and the asymptotic dimensiongrad are equal in the class of r-convex metric spaces. This class…

Geometric Topology · Mathematics 2014-11-04 Sh. Kalantari , B. Honari

Object of investigation are almost hypercomplex manifolds with Hermitian-Norden metrics of the lowest dimension. The considered manifolds are constructed on 4-dimensional Lie groups. It is established a relation between the classes of a…

Differential Geometry · Mathematics 2021-03-16 Hristo Manev

In this paper we consider a special class of polymorphisms with invariant measure, - (cf.[1])- the algebraic polymorphisms of compact groups. A general polymorphism is -- by definition -- a many-valued map with invariant measure, and the…

Dynamical Systems · Mathematics 2007-05-28 Klaus Schmidt , Anatoly Vershik

A classical result of Carleman, based on the theory of quasianalytic functions, shows that polynomials are dense in $L^2(\mu)$ for any $\mu$ such that the moments $\int x^k d\mu$ do not grow too rapidly as $k \to \infty$. In this work, we…

Probability · Mathematics 2025-12-05 Frederic Koehler , Beining Wu

In previous work, a class of noninvertible topological dynamical systems $f: X \to X$ was introduced and studied; we called these {\em topologically coarse expanding conformal} systems. To such a system is naturally associated a preferred…

Dynamical Systems · Mathematics 2013-02-11 Peter Haissinsky , Kevin M. Pilgrim

The multilevel Monte Carlo (MLMC) method has proven to be an effective variance-reduction statistical method for Uncertainty quantification in PDE models. It combines approximations at different levels of accuracy using a hierarchy of…

Numerical Analysis · Mathematics 2019-11-28 Santiago Badia , Jerrad Hampton , Javier Principe