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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

We present eigenvalue decay estimates of integral operators associated with compositional dot-product kernels. The estimates improve on previous ones established for power series kernels on spheres. This allows us to obtain the volumes of…

Machine Learning · Statistics 2021-03-01 Meyer Scetbon , Zaid Harchaoui

The Riemannian metric on the manifold of positive definite matrices is defined by a kernel function $\phi$ in the form $K_D^\phi(H,K)=\sum_{i,j}\phi(\lambda_i,\lambda_j)^{-1} Tr P_iHP_jK$ when $\sum_i\lambda_iP_i$ is the spectral…

Mathematical Physics · Physics 2008-11-08 F. Hiai , D. Petz

We develop a framework for function classes generated by parametric ridge kernels: one-dimensional kernels composed with affine projections and averaged over a parameter measure. The induced kernels are positive definite, and the resulting…

Functional Analysis · Mathematics 2025-08-26 James Tian

It is a well-known and easily established fact that every Euclidean domain is also a principal ideal domain. However, the converse statement is not true, and this is usually shown by exhibiting as a counterexample the ring of algebraic…

Commutative Algebra · Mathematics 2025-11-10 Nicolás Allo-Gómez

$C^*$-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

We consider kernel methods on general geodesic metric spaces and provide both negative and positive results. First we show that the common Gaussian kernel can only be generalized to a positive definite kernel on a geodesic metric space if…

Machine Learning · Computer Science 2014-11-18 Aasa Feragen , Francois Lauze , Søren Hauberg

We study positive definite kernels pulled back along a finite family of self-maps under a subinvariance inequality for the associated branching operator. Iteration produces an increasing kernel tower with defect kernels. Under diagonal…

Probability · Mathematics 2026-02-03 James Tian

We prove that the optimal assignment kernel, proposed recently as an attempt to embed labeled graphs and more generally tuples of basic data to a Hilbert space, is in fact not always positive definite.

Machine Learning · Computer Science 2008-01-29 Jean-Philippe Vert

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

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

An algebraic investigation on bicomplex numbers is carried out here. Particularly matrices and linear maps defined on them are discussed. A new kind of cartesian product, referred to as an idempotent product, is introduced and studied. The…

Representation Theory · Mathematics 2023-12-04 Anjali , Fahed Zulfeqarr , Akhil Prakash , Prabhat Kumar

Given a fixed sigma-finite measure space $\left(X,\mathscr{B},\nu\right)$, we shall study an associated family of positive definite kernels $K$. Their factorizations will be studied with view to their role as covariance kernels of a variety…

Spectral Theory · Mathematics 2018-10-31 Palle Jorgensen , Feng Tian

Kernel matrices are of central importance to many applied fields. In this manuscript, we focus on spectral properties of kernel matrices in the so-called ``flat limit'', which occurs when points are close together relative to the scale of…

Numerical Analysis · Mathematics 2025-03-28 Simon Barthelmé , Konstantin Usevich

We study the positive-definiteness of a family of $L^2(\mathbf{R})$ integral operators with kernel $K_{t, a}(x, y) = (1 + (x - y)^2 + a(x^2 + y^2)^t)^{-1}$, with $t > 0$ and $a > 0$. When $0 < t \le 1$, the known theory of positive-definite…

Functional Analysis · Mathematics 2021-05-17 Charles E. Baker

We review machine learning methods employing positive definite kernels. These methods formulate learning and estimation problems in a reproducing kernel Hilbert space (RKHS) of functions defined on the data domain, expanded in terms of a…

Statistics Theory · Mathematics 2009-09-29 Thomas Hofmann , Bernhard Schölkopf , Alexander J. Smola

We present natural families of coordinate algebras of noncommutative products of Euclidean spaces. These coordinate algebras are quadratic ones associated with an R-matrix which is involutive and satisfies the Yang-Baxter equations. As a…

Quantum Algebra · Mathematics 2018-05-23 Michel Dubois-Violette , Giovanni Landi

We construct examples of non-isomorphic algebraic vector bundles on the punctured affine space with isomorphic pullbacks to the smooth quadric.

Group Theory · Mathematics 2013-03-05 Brent Doran , Jun Yu

The study of representations invariant to common transformations of the data is important to learning. Most techniques have focused on local approximate invariance implemented within expensive optimization frameworks lacking explicit…

Machine Learning · Computer Science 2017-02-27 Dipan K. Pal , Marios Savvides

We study positive kernels on $X\times X$, where $X$ is a set equipped with an action of a group, and taking values in the set of $\mathcal A$-sesquilinear forms on a (not necessarily Hilbert) module over a $C^*$-algebra $\mathcal A$. These…

Operator Algebras · Mathematics 2021-01-22 Erkka Haapasalo , Juha-Pekka Pellonpää