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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 survey results concerning behavior of positivity of line bundles and possible vanishing theorems in positive characteristic. We also try to describe variation of positivity in mixed characteristic. These problems are very much related to…

Algebraic Geometry · Mathematics 2015-03-24 Adrian Langer

The present work develops certain analytical tools required to construct and compute invariant kernels on the space of complex covariance matrices. The main result is the $\mathrm{L}^1$--Godement theorem, which states that any invariant…

Functional Analysis · Mathematics 2025-04-17 Salem Said , Franziskus Steinert , Cyrus Mostajeran

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

A rectangular matrix is called totally positive, if all its minors are positive. A point of a real Grassmanian manifold $G_{l,m}$ of $l$-dimensional subspaces in $\mathbb R^m$ is called strictly totally positive, if one can normalize its…

Dynamical Systems · Mathematics 2018-05-10 Victor Buchstaber , Alexey Glutsyuk

We establish a domination principle for positive operators, which provides an upper bound on the essential spectral radius and yields quasi-compactness criteria on weighted supremum spaces with Lyapunov type functions and local domination.…

Probability · Mathematics 2026-01-12 Denis Villemonais

This work aims to prove that the classical Gaussian kernel, when defined on a non-Euclidean symmetric space, is never positive-definite for any choice of parameter. To achieve this goal, the paper develops new geometric and analytical…

Machine Learning · Computer Science 2024-09-09 Nathael Da Costa , Cyrus Mostajeran , Juan-Pablo Ortega , Salem Said

We study the positivity and asymptotic behaviour of nonnegative solutions of a general nonlocal fast diffusion equation, \[\partial_t u + \mathcal{L}\varphi(u) = 0,\] and the interplay between these two properties. Here $\mathcal{L}$ is a…

Analysis of PDEs · Mathematics 2024-03-12 Arturo de Pablo , Fernando Quirós , Jorge Ruiz-Cases

Let G be a simple and simply-connected complex algebraic group, and let X \subset G^\vee be the centralizer subgroup of a principal nilpotent element. Ginzburg and Peterson independently related the ring of functions on X with the homology…

Representation Theory · Mathematics 2012-04-26 Thomas Lam , Konstanze Rietsch

We study kernel quadrature rules with convex weights. Our approach combines the spectral properties of the kernel with recombination results about point measures. This results in effective algorithms that construct convex quadrature rules…

Numerical Analysis · Mathematics 2022-10-12 Satoshi Hayakawa , Harald Oberhauser , Terry Lyons

We present sufficient condition for a family of positive definite kernels on a compact two-point homogeneous space to be strictly positive definite based on their representation as a series of spherical harmonics. The family analyzed is a…

Classical Analysis and ODEs · Mathematics 2022-05-17 Jean Carlo Guella , Janin Jäger

In this paper we continue to investigate a certain class of Hankel-like positive definite kernels using their associated orthogonal polynomials. The main result of this paper is about the structure of this kind of kernels.

Functional Analysis · Mathematics 2007-05-23 T. Banks , T. Constantinescu

Interpolation and approximation of functionals with conditionally positive definite kernels is considered on sets of centers that are not determining for polynomials. It is shown that polynomial consistency is sufficient in order to define…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov

Fractional powers and polynomial maps preserving structured totally positive matrices, one-sided Polya frequency functions, or totally positive kernels are treated from a unifying perspective. Besides the stark rigidity of the polynomial…

Functional Analysis · Mathematics 2022-08-19 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

We consider positive semidefinite kernels valued in the $*$-algebra of adjointable operators on a VE-space (Vector Euclidean space) and that are invariant under actions of $*$-semigroups. A rather general dilation theorem is stated and…

Functional Analysis · Mathematics 2017-02-06 Serdar Ay , Aurelian Gheondea

In this article we study the field of Hilbertian metrics and positive definit (pd) kernels on probability measures, they have a real interest in kernel methods. Firstly we will make a study based on the Alpha-Beta-divergence to have a…

Methodology · Statistics 2018-09-18 Mactar Ndaw , Macoumba Ndour , Papa Ngom

$C^*$-algebra-valued kernels could pave the way for the next generation of kernel machines. To further our fundamental understanding of learning with $C^*$-algebraic kernels, we propose a new class of positive definite kernels based on the…

Machine Learning · Statistics 2025-03-11 Yuka Hashimoto , Ayoub Hafid , Masahiro Ikeda , Hachem Kadri

It is well known that positivity properties of the curvature of a vector bundle have implications on the algebro-geometric properties of the bundle, such as numerical positivity, vanishing of higher cohomology leading to existence of global…

Algebraic Geometry · Mathematics 2018-10-12 Mark Green , Phillip Griffiths

This paper studies random operator-valued positive definite (p.d.) kernels and their connection to moment dilations. A class of random p.d. kernels is introduced in which the positivity requirement is imposed only in expectation, extending…

Functional Analysis · Mathematics 2025-08-15 James Tian

We develop a new method that enables us to solve the open problem of characterizing discrete inequalities for kernel operators involving suprema. More precisely, we establish necessary and sufficient conditions under which there exists a…

Functional Analysis · Mathematics 2022-07-20 Amiran Gogatishvili , Luboš Pick , Tuğçe Ünver