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We establish endpoint Lebesgue space bounds for convolution and restricted X-ray transforms along curves satisfying fairly minimal differentiability hypotheses, with affine and Euclidean arclengths. We also explore the behavior of certain…

Classical Analysis and ODEs · Mathematics 2017-10-24 Spyridon Dendrinos , Betsy Stovall

We study reproducing kernel Hilbert spaces (RKHS) on a Riemannian manifold. In particular, we discuss under which condition Sobolev spaces are RKHS and characterize their reproducing kernels. Further, we introduce and discuss a class of…

Functional Analysis · Mathematics 2019-05-28 Ernesto De Vito , Nicole Mücke , Lorenzo Rosasco

This paper establishes the first polynomial convergence rates for Gaussian kernel ridge regression (KRR) with a fixed hyperparameter in both the uniform and the $L^{2}$-norm. The uniform convergence result closes a gap in the theoretical…

Machine Learning · Statistics 2025-09-12 Paul Dommel , Rajmadan Lakshmanan

To help understand various reproducing kernels used in applied sciences, we investigate the inclusion relation of two reproducing kernel Hilbert spaces. Characterizations in terms of feature maps of the corresponding reproducing kernels are…

Functional Analysis · Mathematics 2011-06-22 Haizhang Zhang , Liang Zhao

In this paper, we establish a demi-distributions theory which develops the usual distribution theory, in particular, we show that many conclusions as differentiations, Fourier transforms and convolutions can be generalized to the…

Functional Analysis · Mathematics 2021-05-05 Ronglu Li , Shuhui Zhong , Dohan Kim , Junde Wu

The little q-Jacobi function transform depends on three parameters. An explicit expression as a sum of two very-well-poised 8W7-series is derived for the dual transmutation kernel (a kind of non-symmetric Poisson kernel) relating little…

Classical Analysis and ODEs · Mathematics 2007-05-23 Erik Koelink , Hjalmar Rosengren

In this paper, we introduce a new image representation based on a multilayer kernel machine. Unlike traditional kernel methods where data representation is decoupled from the prediction task, we learn how to shape the kernel with…

Machine Learning · Statistics 2016-10-26 Julien Mairal

A covariant scattering kernel is a core component in any self-consistent general relativistic radiative transfer formulation in scattering media. An explicit closed-form expression for a covariant Compton scattering kernel with a good…

High Energy Astrophysical Phenomena · Physics 2015-06-16 Ziri Younsi , Kinwah Wu

The rapid development of reliable Quantum Processing Units (QPU) opens up novel computational opportunities for machine learning. Here, we introduce a procedure for measuring the similarity between graph-structured data, based on the…

Quantum Physics · Physics 2021-09-29 Louis-Paul Henry , Slimane Thabet , Constantin Dalyac , Loïc Henriet

Quantum groups at roots of unity have the property that their centre is enlarged. Polynomial equations relate the standard deformed Casimir operators and the new central elements. These relations are important from a physical point of view…

q-alg · Mathematics 2009-10-30 B. Abdesselam , D. Arnaudon , M. Bauer

Kernel methods have been widely applied to machine learning and other questions of approximating an unknown function from its finite sample data. To ensure arbitrary accuracy of such approximation, various denseness conditions are imposed…

Machine Learning · Statistics 2013-10-25 Benxun Wang , Haizhang Zhang

We present a solution to a problem suggested by Philippe Biane: We prove that a certain Plancherel-type probability distribution on partitions converges, as partitions get large, to a new determinantal random point process on the set…

Probability · Mathematics 2008-03-02 Alexei Borodin , Grigori Olshanski

Novel types of convolution operators for quaternion linear canonical transform (QLCT) are proposed. Type one and two are defined in the spatial and QLCT spectral domains, respectively. They are distinct in the quaternion space and are…

Classical Analysis and ODEs · Mathematics 2022-12-13 Xiaoxiao Hu , Dong Cheng , Kit Ian Kou

Let $K$ be an imaginary quadratic number field of class number one and $\mathcal{O}_K$ be its ring of integers. We show that, if the arithmetic functions $f, g:\mathcal{O}_K\rightarrow \mathbb{C}$ both have level of distribution $\vartheta$…

Number Theory · Mathematics 2018-04-13 Pranendu Darbar , Anirban Mukhopadhyay

Various methods in statistical learning build on kernels considered in reproducing kernel Hilbert spaces. In applications, the kernel is often selected based on characteristics of the problem and the data. This kernel is then employed to…

Machine Learning · Statistics 2024-03-12 Paul Dommel , Alois Pichler

``Quasi-elliptic'' functions can be given a ring structure in two different ways, using either ordinary multiplication, or convolution. The map between the corresponding standard bases is calculated. A related structure has appeared…

Rings and Algebras · Mathematics 2021-05-13 Marianne Leitner

The Dimensional Regularization of Bollini and Giambiags (Phys. Lett. {\bf B 40}, 566 (1972), Il Nuovo Cim. {\bf B 12}, 20 (1972). Phys. Rev. {\bf D 53}, 5761 (1996)) can not be defined for all Schwartz Tempered Distributions Explicitly…

General Physics · Physics 2018-11-30 A. Plastino , M. C. Rocca

The paper deals with point-wise estimates for the heat kernel of a nonlocal convolution type operator with a kernel that decays at least exponentially at infinity. It is shown that the large time behaviour of the heat kernel depends…

Functional Analysis · Mathematics 2018-04-25 Alexander Grigoryan , Yury Kondratiev , Andrey Piatnitski , Elena Zhizhina

Given a $2$-step stratified group which does not satisfy a slight strengthening of the Moore-Wolf condition, a sub-Laplacian $\mathcal{L}$ and a family $\mathcal{T}$ of elements of the derived algebra, we study the convolution kernels…

Functional Analysis · Mathematics 2020-03-31 Mattia Calzi

We define and study distributions in R^{d} that we call q-Normal. For q=1 they are really multidimensional Normal, for q\in(-1,1) they have densities, compact support and many properties that resemble properties of ordinary multidimensional…

Probability · Mathematics 2012-08-13 Paweł J. Szabłowski
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