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Convolution is an important tool in the construction of positive definite kernels on a manifold. This contribution provides conditions on an $L^2$-positive definite and zonal kernel on the unit sphere of $\mathbb{C}^q$ in order that the…

Classical Analysis and ODEs · Mathematics 2015-02-16 Victor S. Barbosa , Valdir A. Menegatto

The seminal theorem of I.J. Schoenberg characterizes positive definite (p.d.) kernels on the unit sphere $S^{n-1}$ invariant under the automorphisms of the sphere. We obtain two generalizations of this theorem for p.d. kernels on fiber…

Classical Analysis and ODEs · Mathematics 2019-04-05 Olga Kuryatnikova , Juan C. Vera

The accuracy and complexity of kernel learning algorithms is determined by the set of kernels over which it is able to optimize. An ideal set of kernels should: admit a linear parameterization (tractability); be dense in the set of all…

Machine Learning · Statistics 2020-05-04 Brendon K. Colbert , Matthew M. Peet

We define a family of kernels for mixed continuous/discrete hierarchical parameter spaces and show that they are positive definite.

Machine Learning · Statistics 2013-10-23 Frank Hutter , Michael A. Osborne

The paper introduces a new characterisation of strictly positive definiteness for kernels on the 2-sphere without assuming the kernel to be radially (isotropic) or axially symmetric. The results use the series expansion of the kernel in…

Numerical Analysis · Mathematics 2022-05-06 Janin Jäger

We introduce a method to construct general multivariate positive definite kernels on a nonempty set $X$ that employs a prescribed bounded completely monotone function and special multivariate functions on $X$.\ The method is consistent with…

Functional Analysis · Mathematics 2021-06-29 V. A. Menegatto , C. P. Oliveira

This survey is an introduction to positive definite kernels and the set of methods they have inspired in the machine learning literature, namely kernel methods. We first discuss some properties of positive definite kernels as well as…

Machine Learning · Statistics 2009-12-04 Marco Cuturi

We initiate the effective metric structure theory of Keisler randomizations. We show that a classical countable structure $\mathcal{M}$ has a decidable presentation if and only if its Borel randomization $\mathcal{M}^{[0,1)}$ has a…

Logic · Mathematics 2025-06-09 Nicolás Cuervo Ovalle , Isaac Goldbring

The paper introduces new sufficient conditions of strict positive definiteness for kernels on d-dimensional spheres which are not radially symmetric but possess specific coefficient structures. The results use the series expansion of the…

Numerical Analysis · Mathematics 2021-05-07 Martin Buhmann , Janin Jäger

We provide a characterization for the continuous positive definite kernels on $\mathbb R^d$ that are invariant to linear isometries, i.e. invariant under the orthogonal group $O(d)$. Furthermore, we provide necessary and sufficient…

Statistics Theory · Mathematics 2025-06-30 Felix Benning , Max David Schölpple

This survey contains a selection of topics unified by the concept of positive semi-definiteness (of matrices or kernels), reflecting natural constraints imposed on discrete data (graphs or networks) or continuous objects (probability or…

Classical Analysis and ODEs · Mathematics 2019-11-13 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

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

We show that a formal power series in $2N$ non-commuting indeterminates is a positive non-commutative kernel if and only if the kernel on $N$-tuples of matrices of any size obtained from this series by matrix substitution is positive. We…

Functional Analysis · Mathematics 2007-05-23 Dmitry S. Kalyuzhny\uı-Verbovetzki\uı , Victor Vinnikov

We study how iterated and composed completely positive maps act on operator-valued kernels. Each kernel is realized inside a single Hilbert space where composition corresponds to applying bounded creation operators to feature vectors. This…

Functional Analysis · Mathematics 2025-11-18 James Tian

We prove that for every radial weighted Fock space, the system biorthogonal to a complete and minimal system of reproducing kernels is also complete under very mild regularity assumptions on the weight. This result generalizes a theorem by…

Complex Variables · Mathematics 2018-03-14 Anton Baranov , Yurii Belov , Alexander Borichev

The composition operators preserving total non-negativity and total positivity for various classes of kernels are classified, following three themes. Letting a function act by post composition on kernels with arbitrary domains, it is shown…

Functional Analysis · Mathematics 2023-09-27 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

A class of negative definite kernels is defined in terms of measure spaces. Using this concept, property (T) for a countable group $\G$ is characterized in terms of measure preserving actions of $\G$, as follows. If a set $S$ is translated…

Functional Analysis · Mathematics 2013-02-26 Guyan Robertson , Tim Steger

We characterize the reproducing kernel Hilbert spaces whose elements are $p$-integrable functions in terms of the boundedness of the integral operator whose kernel is the reproducing kernel. Moreover, for $p=2$ we show that the spectral…

Functional Analysis · Mathematics 2007-05-23 Claudio Carmeli , Ernesto De Vito , Alessandro Toigo

In analogy to the classical isomorphism between $\mathcal{L}(\mathcal{S}(\mathbb{R}^{n}) ,\mathcal{S}^{\prime}(\mathbb{R}^{m}) ) $ and $\mathcal{S}^{\prime}(\mathbb{R}^{n+m}) $, we show that a large class of moderate linear mappings acting…

Functional Analysis · Mathematics 2009-04-18 Antoine Delcroix

We generalize the following univariate characterization of the Kummer and Gamma distributions to the cone of symmetric positive definite matrices: let $X$ and $Y$ be independent, non-degenerate random variables valued in $(0, \infty)$, then…

Probability · Mathematics 2018-05-16 Agnieszka Piliszek , Bartosz Kołodziejek