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We investigate the intertwining of Laguerre processes of parameter $\alpha$ in different dimensions. We introduce a Feller kernel that depends on $\alpha $ and intertwines the $\alpha$-Laguerre process in $N+1$ dimensions and that in $N$…

Probability · Mathematics 2024-03-19 Alexander I. Bufetov , Yosuke Kawamoto

The main result of this paper, Theorem 1.5, establishes a conjecture of Lyons and Peres: for a determinantal point process governed by a reproducing kernel, the system of kernels sampled at the particles of a random configuration is…

Probability · Mathematics 2018-12-19 Alexander I. Bufetov , Yanqi Qiu , Alexander Shamov

We give a new expression for the inner product of two kernel functions associated to a cusp form. Among other applications, it yields an extension of a formula of Kohnen and Zagier, and another proof of Manin's Periods Theorem. Cohen's…

Number Theory · Mathematics 2009-08-18 Nikolaos Diamantis , Cormac O'Sullivan

The main purpose of this paper is to introduce a new sequence space by using de la Vallee-Poussin mean and investigate both the modular structure with some geometric properties and some topological properties with respect to the Luxemburg…

Functional Analysis · Mathematics 2009-10-13 Necip Simsek , Ekrem Savas , Vatan Karakaya

The matrix Whittaker kernel has been introduced by A. Borodin in Part IV of the present series of papers. This kernel describes a point process -- a probability measure on a space of countable point configurations. The kernel is expressed…

Representation Theory · Mathematics 2007-05-23 Grigori Olshanski

Bourgain in his seminal paper [2] about the analysis of maximal functions associated to convex bodies, has estimated in a sharp way the $L^2$-operator norm of the maximal function associated to a kernel $K\in L^1,$ with differentiable…

Functional Analysis · Mathematics 2024-01-23 Duván Cardona

We give an interpretation of the $(q,t)$-deformed Cartan matrices of finite type and their inverses in terms of bigraded modules over the generalized preprojective algebras of Langlands dual type in the sense of Gei\ss-Leclerc-Schr\"{o}er…

Representation Theory · Mathematics 2022-03-31 Ryo Fujita , Kota Murakami

For the multivariate trigonometric polynomials we study convolution with the corresponding the de la Vallee Poussin kernel from the point of view of discretization. In other words, we replace the normalized Lebesgue measure by a discrete…

Numerical Analysis · Mathematics 2022-01-04 V. N. Temlyakov

We study divergence properties of Fourier series on Cantor-type fractal measures, also called mock Fourier series. We show that in some cases the $L^1$-norm of the corresponding Dirichlet kernel grows exponentially fast, and therefore the…

Functional Analysis · Mathematics 2012-09-05 Dorin Ervin Dutkay , Deguang Han , Qiyu Sun

Defant, Engen, and Miller defined a refinement of Lassalle's sequence $A_{k+1}$ by considering uniquely sorted permutations of length $2k+1$ whose first element is $\ell$. They showed that each such sequence is symmetric in $\ell$ and…

Combinatorics · Mathematics 2020-08-20 Mihir Singhal

In this paper, we consider norm convergence for a special matrix-based de la Vall\'ee Poussin-like mean of Fourier series for the Walsh system. We estimate the difference between the named mean above and the corresponding function in norm,…

Classical Analysis and ODEs · Mathematics 2023-06-14 István Blahota

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

Determinantal point processes are point processes whose correlation functions are given by determinants of matrices. The entries of these matrices are given by one fixed function of two variables, which is called the kernel of the point…

Classical Analysis and ODEs · Mathematics 2019-06-27 Marco Stevens

We introduce the set of quantum channels with constant Frobenius norm, the set of diagonal channels and the notion of equivalence of one-parameter families of channels. First, we show that all diagonal $2$-dimensional channels with constant…

Quantum Physics · Physics 2019-08-08 Ivan Sergeev

Recently a characterization of uniformly continuous POVMs and a necessary condition for a uniformly continuous POVM $F$ to have the norm-1 property have been provided. Moreover it was proved that in the commutative case, uniform continuity…

Quantum Physics · Physics 2015-06-16 Roberto Beneduci

Starting from de la Vall\'ee Poussin type (VP) interpolation, the authors have recently introduced a family of interpolating polynomial scaling and wavelet bases generating the approximation and detail spaces of a non-standard…

Numerical Analysis · Mathematics 2026-02-25 Woula Themistoclakis , Marc Van Barel

This is an attempt of a comprehensive survey of the results in which estimates of the norms of linear means of multiple Fourier series, the Lebesgue constants, are obtained by means of estimating the Fourier transform of a function…

funct-an · Mathematics 2008-02-03 Elijah Liflyand

In this paper we propose a family of tractable kernels that is dense in the family of bounded positive semi-definite functions (i.e. can approximate any bounded kernel with arbitrary precision). We start by discussing the case of stationary…

Machine Learning · Statistics 2015-10-13 Yves-Laurent Kom Samo , Stephen Roberts

In parameterized algorithmics, the process of kernelization is defined as a polynomial time algorithm that transforms the instance of a given problem to an equivalent instance of a size that is limited by a function of the parameter. As,…

Computational Complexity · Computer Science 2019-03-01 Jouke Witteveen , Ralph Bottesch , Leen Torenvliet

We consider the least-square regression problem with regularization by a block 1-norm, i.e., a sum of Euclidean norms over spaces of dimensions larger than one. This problem, referred to as the group Lasso, extends the usual regularization…

Machine Learning · Computer Science 2008-01-28 Francis Bach
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