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Let us say that an $n$-sided polygon is semi-regular if it is circumscriptible and its angles are all equal but possibly one, which is then larger than the rest. Regular polygons, in particular, are semi-regular. We prove that semi-regular…

Spectral Theory · Mathematics 2017-09-19 Alberto Enciso , Javier Gómez-Serrano

An infinitely wide model is a weighted integration $\int \varphi(x,v) d \mu(v)$ of feature maps. This model excels at handling an infinite number of features, and thus it has been adopted to the theoretical study of deep learning. Kernel…

Machine Learning · Statistics 2020-07-08 Sho Sonoda

Kernel methods are powerful machine learning techniques which implement generic non-linear functions to solve complex tasks in a simple way. They Have a solid mathematical background and exhibit excellent performance in practice. However,…

Machine Learning · Computer Science 2021-01-27 J. Emmanuel Johnson , Valero Laparra , Adrián Pérez-Suay , Miguel D. Mahecha , Gustau Camps-Valls

It is well known that a hyperbolic domain in the complex plane has uniformly perfect boundary precisely when the product of its hyperbolic density and the distance function to its boundary has a positive lower bound. We extend this…

Complex Variables · Mathematics 2015-03-06 Toshiyuki Sugawa

Let G be a bounded Jordan domain in the complex plane with piecewise analytic boundary. We present theoretical estimates and numerical evidence for certain phenomena, regarding the application of the Bergman kernel method with algebraic and…

Numerical Analysis · Mathematics 2011-01-04 M. Lytrides , N. Stylianopoulos

We propose efficient random features for approximating a new and rich class of kernel functions that we refer to as Generalized Zonal Kernels (GZK). Our proposed GZK family, generalizes the zonal kernels (i.e., dot-product kernels on the…

Machine Learning · Computer Science 2022-02-09 Insu Han , Amir Zandieh , Haim Avron

The global geometry of the universe is in principle as observable an attribute as local curvature. Previous studies have established that if the universe is wrapped into a flat hypertorus, the simplest compact space, then the fundamental…

Astrophysics · Physics 2009-10-30 Janna Levin , Evan Scannapieco , Joseph Silk

Let $H$ be a finite dimensional hereditary algebra over an algebraically closed field, and let $\mathcal{C}_{H}$ be the corresponding cluster category. We give a description of the (standard) fundamental domain of $\mathcal{C}_{H} $ in the…

Representation Theory · Mathematics 2011-12-30 Juan Ángel Cappa , Maria Inés Platzeck , Idun Reiten

We consider a convenient category of "quadratic" multirings, that allows simple functorial relations with categories associated with abstract quadratic forms theories and shares many good aspects of the theories of Special Groups and of…

Rings and Algebras · Mathematics 2017-03-30 Kaique Matias de Andrade Roberto , Hugo Rafael Ribeiro , Hugo Luiz Mariano

We show that kernel-based quadrature rules for computing integrals can be seen as a special case of random feature expansions for positive definite kernels, for a particular decomposition that always exists for such kernels. We provide a…

Machine Learning · Computer Science 2015-11-10 Francis Bach

Non-relativistic particles that are effectively confined to two dimensions can in general move on curved surfaces, allowing dynamical phenomena beyond what can be described with scalar potentials or even vector gauge fields. Here we…

Quantum Physics · Physics 2022-11-15 James R. Anglin , Etienne Wamba

It has been hypothesized that quantum computers may lend themselves well to applications in machine learning. In the present work, we analyze function classes defined via quantum kernels. Quantum computers offer the possibility to…

Quantum Physics · Physics 2021-11-10 Jonas M. Kübler , Simon Buchholz , Bernhard Schölkopf

Planar linkages are a rich area of study motivated by practical applications in engineering mechanisms. A central result is Kempe's Universality Theorem, which states that semi-algebraic sets can be realized by planar linkages. Polyhedral…

Combinatorics · Mathematics 2025-02-25 Robert Miranda

Quantum kernel methods are a promising branch of quantum machine learning, yet their effectiveness on diverse, high-dimensional, real-world data remains unverified. Current research has largely been limited to low-dimensional or synthetic…

Machine Learning · Computer Science 2026-02-19 Jiang Yuhan , Matthew Otten

The fundamental properties of biquaternions (complexified quaternions) are presented including several different representations, some of them new, and definitions of fundamental operations such as the scalar and vector parts, conjugates,…

Rings and Algebras · Mathematics 2015-06-25 Stephen J. Sangwine , Todd A. Ell , Nicolas Le Bihan

Functionals (i.e. functions of functions) are widely used in quantum field theory and solid-state physics. In this paper, functionals are given a rigorous mathematical framework and their main properties are described. The choice of the…

Mathematical Physics · Physics 2018-03-14 Christian Brouder , Nguyen Viet Dang , Camille Laurent-Gengoux , Kasia Rejzner

A completely well-centered tetrahedral mesh is a triangulation of a three dimensional domain in which every tetrahedron and every triangle contains its circumcenter in its interior. Such meshes have applications in scientific computing and…

Computational Geometry · Computer Science 2008-08-06 Evan VanderZee , Anil N. Hirani , Damrong Guoy

Let X be a finite CW complex or compact Lipschitz neighborhood retract with universal cover Z; let M be a compact orientable manifold of dimension at least 2 and nonempty boundary. We establish the existence of an isoperimetric profile for…

Group Theory · Mathematics 2009-01-16 Chad Groft

We consider Bergman spaces and variations of them in one or several complex variables. For some domains we show that in these spaces the generic function is totally unbounded and hence non - extendable. We also show that the generic…

Complex Variables · Mathematics 2017-04-10 T. Hatziafratis , K. Kioulafa , V. Nestoridis

Positive-definite kernel functions are fundamental elements of kernel methods and Gaussian processes. A well-known construction of such functions comes from Bochner's characterization, which connects a positive-definite function with a…

Machine Learning · Statistics 2016-10-28 Jie Chen , Dehua Cheng , Yan Liu