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We connect shift-invariant characteristic kernels to infinitely divisible distributions on $\mathbb{R}^{d}$. Characteristic kernels play an important role in machine learning applications with their kernel means to distinguish any two…

Machine Learning · Statistics 2016-10-26 Yu Nishiyama , Kenji Fukumizu

In this work we analyze a convex-programming method for estimating superpositions of point sources or spikes from nonuniform samples of their convolution with a known kernel. We consider a one-dimensional model where the kernel is either a…

Optimization and Control · Mathematics 2018-06-04 Brett Bernstein , Carlos Fernandez-Granda

I continue the investigation of a q-analogue of the convolution on the line started in a joint work with Koornwinder and based on a formal definition due to Kempf and Majid. Two different ways of approximating functions by means of the…

Classical Analysis and ODEs · Mathematics 2016-09-07 Giovanna Carnovale

In this paper, using a quantum superalgebra associated with the universal central extension of sl(2,2)^{(1)}, we introduce new R-matrices having an extra parameter x. As x\to 0, they become those associated with the symmetric and…

Quantum Algebra · Mathematics 2015-06-26 Hiroyuki Yamane

We completely characterize the class of univariate distributions allowing for a Stein kernel and illustrate our result by means of some concrete distributions. Moreover, we apply our findings to prove a quantitative version of the central…

Probability · Mathematics 2025-02-19 Christian Döbler

The aim of this paper is to construct sup-exponentially localized kernels and frames in the context of classical orthogonal expansions, namely, expansions in Jacobi polynomials, spherical harmonics, orthogonal polynomials on the ball and…

Classical Analysis and ODEs · Mathematics 2008-09-22 Kamen Ivanov , Pencho Petrushev , Yuan Xu

The role of kernels is central to machine learning. Motivated by the importance of power-law distributions in statistical modeling, in this paper, we propose the notion of power-law kernels to investigate power-laws in learning problem. We…

Machine Learning · Computer Science 2013-04-02 Debarghya Ghoshdastidar , Ambedkar Dukkipati

The paper is devoted to infinite Bernoulli convolutions generated by positive multigeometric series and to probability distributions of random variables whose digits in an even integer base-$s$ expansion with two redundant digits form a…

Probability · Mathematics 2026-03-13 Mykola Pratsiovytyi , Dmytro Karvatskyi , Oleg Makarchuk

We introduce gauge-invariant quark and gluon angular momentum distributions after making a generalization of the angular momentum density operators. From the quark angular momentum distribution, we define the gauge-invariant and…

High Energy Physics - Phenomenology · Physics 2009-10-31 Pervez Hoodbhoy , Xiangdong Ji , Wei Lu

In this article, we explore convolutions of distributions with distributions given by (weighted) line integration. We also explore the scattering of singularities of such convolutions.

Analysis of PDEs · Mathematics 2015-07-27 Brian Sherson

Let $E$ be an $1$-Ahlfors regular subset of the Heisenberg group $\mathbb{H}$. We prove that there exists a $-1$-homogeneous kernel $K_1$ such that if $E$ is contained in a $1$-regular curve the corresponding singular integral is bounded in…

Classical Analysis and ODEs · Mathematics 2019-09-17 Vasileios Chousionis , Sean Li

Kernel methods for deconvolution have attractive features, and prevail in the literature. However, they have disadvantages, which include the fact that they are usually suitable only for cases where the error distribution is infinitely…

Statistics Theory · Mathematics 2009-09-29 Peter Hall , Alexander Meister

The radially deformed Fourier transform, introduced in [S. Ben Said, T. Kobayashi and B. Orsted, Laguerre semigroup and Dunkl operators, Compositio Math.], is an integral transform that depends on a numerical parameter $a \in R^{+}$. So…

Classical Analysis and ODEs · Mathematics 2013-04-30 Hendrik De Bie

Bessel-type convolution algebras of bounded Borel measures on the matrix cones of positive semidefinite $q\times q$-matrices over $\mathbb R, \mathbb C, \mathbb H$ were introduced recently by R\"osler. These convolutions depend on some…

Classical Analysis and ODEs · Mathematics 2012-01-18 Michael Voit

We derive asymptotic normality of kernel type deconvolution density estimators. In particular we consider deconvolution problems where the known component of the convolution has a symmetric lambda-stable distribution, 0<lambda<= 2. It turns…

Statistics Theory · Mathematics 2007-06-13 A. J. van Es , H. -W. Uh

This paper presents a parametric family of compactly-supported positive semidefinite kernels aimed to model the covariance structure of second-order stationary isotropic random fields defined in the $d$-dimensional Euclidean space. Both the…

Statistics Theory · Mathematics 2021-01-26 Xavier Emery , Alfredo Alegría

Let $X_1,...,X_n$ be i.i.d. observations, where $X_i=Y_i+\sigma Z_i$ and $Y_i$ and $Z_i$ are independent. Assume that unobservable $Y$'s are distributed as a random variable $UV,$ where $U$ and $V$ are independent, $U$ has a Bernoulli…

Statistics Theory · Mathematics 2008-04-30 Bert van Es , Shota Gugushvili , Peter Spreij

It is well-known that univariate cubic spline interpolation, if carried out on point sets with fill distance $h$, converges only like ${\cal O}(h^2)$ in $L_2[a,b]$ for functions in $W_2^2[a,b]$ if no additional assumptions are made. But…

Numerical Analysis · Mathematics 2016-07-15 Robert Schaback

The paper deals with singular Sturm-Liouville expressions with matrix-valued distributional coefficients. Due to a suitable regularization, the corresponding operators are correctly defined as quasi-differentials. Their resolvent…

Functional Analysis · Mathematics 2016-12-14 Alexei Konstantinov , Oleksandr Konstantinov

We study distributions on a Euclidean Jordan algebra V with values in a finite dimensional representation space for the identity component G of the structure group of V and homogeneous equivariance condition. We show that such distributions…

Functional Analysis · Mathematics 2007-05-23 Bruno Blind