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Kernel methods in machine learning use a kernel function that takes two data points as input and returns their inner product after mapping them to a Hilbert space, implicitly and without actually computing the mapping. For many kernel…

Machine Learning · Computer Science 2024-10-17 Kamaledin Ghiasi-Shirazi , Mohammadreza Qaraei

We extend the theory of Euler integration from the class of constructible functions to that of "tame" real-valued functions (definable with respect to an o-minimal structure). The corresponding integral operator has some unusual defects (it…

General Topology · Mathematics 2015-05-14 Y. Baryshnikov , R. Ghrist

Finite Euler hierarchies of field theory Lagrangians leading to universal equations of motion for new types of string and membrane theories and for {\it classical} topological field theories are constructed. The analysis uses two main…

High Energy Physics - Theory · Physics 2009-10-22 D. B. Fairlie , J. Govaerts

The neural tangent kernel is a kernel function defined over the parameter distribution of an infinite width neural network. Despite the impracticality of this limit, the neural tangent kernel has allowed for a more direct study of neural…

Machine Learning · Statistics 2025-10-09 Ronaldas Paulius Lencevičius

Given a complex nilpotent finite dimensional Lie algebra of linear transformations $L$, in a complex finite dimensional vector space $E$, we study the joint spectra $Sp(L,E)$, $\sigma_{\delta,k}(L,E)$ and $\sigma_{\pi,k}(L,E)$. We compute…

Functional Analysis · Mathematics 2016-02-17 Enrico Boasso

The invertibility of integral linear operators is a major problem of both theoretical and practical importance. In this paper we investigate the relation between an operator invertibility and the rank of its integral kernel to develop a…

Functional Analysis · Mathematics 2011-05-27 Nikolay Balov

The kernel method is an essential tool for the study of generating series of walks in the quarter plane. This method involves equating to zero a certain polynomial, the kernel polynomial, and using properties of the curve, the kernel curve,…

Combinatorics · Mathematics 2024-10-22 Thomas Dreyfus , Charlotte Hardouin , Julien Roques , Michael F. Singer

A ladder structure of operators is presented for the associated Legendre polynomials and the spherical harmonics showing that both belong to the same irreducible representation of so(3,2). As both are also bases of square-integrable…

Mathematical Physics · Physics 2015-06-11 E. Celeghini , M. A. del Olmo

The kernel of a pair of linear systems is studied in the framework of commutative ring theory with applications to behavioral perspective of linear systems

Commutative Algebra · Mathematics 2016-03-10 Miguel V. Carriegos , Noemí DeCastro-García , Ángel Luis Muñoz Castañeda

We study the integro-differential operators $L$ with kernels $K(y) = a(y) J(y)$, where $J(y)dy$ is a L\'evy measure on $\bR^d$ (i.e. $\int_{\bR^d}(1\wedge |y|^2)J(y)dy<\infty$) and $a(y)$ is an only measurable function with positive lower…

Analysis of PDEs · Mathematics 2014-02-24 Ildoo Kim , Kyeong-Hun Kim

This paper is concerned with the generalized Euler polynomial matrix $\E^{(\alpha)}(x)$ and the Euler matrix $\E$. Taking into account some properties of Euler polynomials and numbers, we deduce product formulae for $\E^{(\alpha)}(x)$ and…

Number Theory · Mathematics 2018-11-06 Yamilet Quintana , William Ramírez , Alejandro Urieles

In these paper we study the adjacency matrix of some infinite graphs, which we call the shift operator on the $L^p$ space of the graph. In particular, we establish norm estimates, we find the norm for some cases, we decide the triviality of…

Functional Analysis · Mathematics 2020-01-29 Aahan Agrawal , Astrid Berge , Seth Colbert-Pollack , Rubén A. Martínez-Avendaño , Elyssa Sliheet

We solve two main questions on linear structures of (non-)norm-attaining Lipschitz functions. First, we show that for every infinite metric space $M$, the set consisting of Lipschitz functions on $M$ which do not strongly attain their norm…

Functional Analysis · Mathematics 2024-04-12 Geunsu Choi , Mingu Jung , Han Ju Lee , Oscar Roldan

For a Hamiltonian $K \in C^2(\mathbb{R}^{N \times n})$ and a map $u:\Omega \subseteq \mathbb{R}^n \longrightarrow \mathbb{R}^N$, we consider the supremal functional \[ \label{1} \tag{1} E_\infty (u,\Omega) \ :=\…

Analysis of PDEs · Mathematics 2014-07-21 Nikos Katzourakis

We reconsider the theory of Lagrange interpolation polynomials with multiple interpolation points and apply it to linear algebra. For instance, $A$ be a linear operator satisfying a degree $n$ polynomial equation $P(A)=0$. One can see that…

Classical Analysis and ODEs · Mathematics 2022-03-04 Askold Khovanskii , Sushil Singla , Aaron Tronsgard

In this article, a novel approach to learning a complex function which can be written as the system of linear equations is introduced. This learning is grounded upon the observation that solving the system of linear equations by a…

Machine Learning · Computer Science 2018-10-23 Kar-Ann Toh

In this work, we study elliptic curves of the form $E_L: y^2 = x(x-1)(x-L)$, where $L^2-L+1 \in \left(\mathbb{Q}^{\times}\right)^2$ and $L \in \mathbb{Q} \setminus \{0,1\}$. We will show that for almost all quadratic extensions…

Number Theory · Mathematics 2023-06-16 Duc Van Huynh

The Gamma kernel is a projection kernel of the form (A(x)B(y)-B(x)A(y))/(x-y), where A and B are certain functions on the one-dimensional lattice expressed through Euler's Gamma function. The Gamma kernel depends on two continuous…

Probability · Mathematics 2013-03-04 Grigori Olshanski

Consider $L$ a regular Lagrangian, $S$ the canonical semispray, and $h$ the horizontal projector of the canonical nonlinear connection. We prove that if the Lagrangian is constant along the integral curves of the Euler-Lagrange equations…

Differential Geometry · Mathematics 2009-09-14 Ioan Bucataru

The universality properties of kernels characterize the class of functions that can be approximated in the associated reproducing kernel Hilbert space and are of fundamental importance in the theoretical underpinning of kernel methods in…

Machine Learning · Computer Science 2025-06-25 Franziskus Steinert , Salem Said , Cyrus Mostajeran