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Related papers: On Banachic Kernels and Approximation Theory

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In this paper, we introduce the notion of reproducing kernel Hilbert spaces for graphs and the Gram matrices associated with them. Our aim is to investigate the Gram matrices of reproducing kernel Hilbert spaces. We provide several bounds…

Combinatorics · Mathematics 2012-12-19 Michio Seto , Sho Suda , Tetsuji Taniguchi

This paper deals with q-analogue of sampling theory associated with q-Dirac system. We derive sampling representation for transform whose kernel is a solution of this q-Dirac system. As a special case, three examples are given.

Classical Analysis and ODEs · Mathematics 2019-01-10 Fatma Hıra

The polynomial kernels are widely used in machine learning and they are one of the default choices to develop kernel-based classification and regression models. However, they are rarely used and considered in numerical analysis due to their…

The goal of this note is to show that continuous functions may be approximated using scattered translates of the Poisson kernel.

Functional Analysis · Mathematics 2025-09-15 Jeff Ledford

This work is concerned with the kernel-based approximation of a complex-valued function from data, where the frequency response function of a partial differential equation in the frequency domain is of particular interest. In this setting,…

Computational Engineering, Finance, and Science · Computer Science 2024-11-26 Julien Bect , Niklas Georg , Ulrich Römer , Sebastian Schöps

This book pretends to compile the latest advances on vector-valued Banach limits as well as their applications to vector-valued almost convergence.

Functional Analysis · Mathematics 2018-01-22 Francisco Javier Garcia-Pacheco , Francisco Javier Perez-Fernandez

In this paper, a new two-parameter family of regularized kernels is introduced, suitable for applying high-order time stepping to N-body systems. These high-order kernels are derived by truncating a Taylor expansion of the non-regularized…

Numerical Analysis · Mathematics 2017-01-09 Benjamin Ong , Andrew Christlieb , Bryan Quaife

We present here a simple and direct proof of the classic geometric version of Hahn-Banach Theorem from its analitic version, in the real case. The reciprocal implication, and the direct proofs of both versions, are already well kown, but…

Functional Analysis · Mathematics 2019-08-28 Fidel José Fernández y Fernández Arroyo

An introduction to the theory of bundle gerbes and their relationship to Hitchin-Chatterjee gerbes is presented. Topics covered are connective structures, triviality and stable isomorphism as well as examples and applications.

Differential Geometry · Mathematics 2008-01-09 Michael K. Murray

What has category theory to offer to Banach spacers? In this second part survey-like paper we will focus on very much needed advanced categorical and homological elements, such as Kan extensions, derived category and derived functor or…

Functional Analysis · Mathematics 2021-10-14 Jesús M. F. Castillo

Variational methods are widely used for approximate posterior inference. However, their use is typically limited to families of distributions that enjoy particular conjugacy properties. To circumvent this limitation, we propose a family of…

Machine Learning · Computer Science 2012-06-22 Samuel Gershman , Matt Hoffman , David Blei

In this article we present a generalization of a Leibniz's geometrical theorem and an application of it.

General Mathematics · Mathematics 2007-10-02 Mihaly Bencze , Florin Popovici , Florentin Smarandache

We formulate and prove a Riemann-Hilbert correspondence between $\hbar$-differential equations and sheaf quantizations, which can be considered as a correspondence between two kinds of quantizations (deformation and sheaf quantization) of…

Symplectic Geometry · Mathematics 2022-02-10 Tatsuki Kuwagaki

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

The Grassmannian manifold G(k, n) serves as a fundamental tool in signal processing, computer vision, and machine learning, where problems often involve classifying, clustering, or comparing subspaces. In this work, we propose a…

Signal Processing · Electrical Eng. & Systems 2025-05-01 Rémi Delogne , Laurent Jacques

We present a practical way of introducing convolutional structure into Gaussian processes, making them more suited to high-dimensional inputs like images. The main contribution of our work is the construction of an inter-domain inducing…

Machine Learning · Statistics 2017-09-07 Mark van der Wilk , Carl Edward Rasmussen , James Hensman

Reproducing kernel Hilbert spaces are uniquely characterized by their kernel, but reproducing kernel Banach spaces (RKBS) are not. However, a characterization of which RKBS admit a given kernel as reproducing kernel is lacking. This work…

Functional Analysis · Mathematics 2026-03-31 Tjeerd Jan Heeringa

We develop a theory of diophantine approximation on generalized flag varieties, varieties that can be obtained as a quotient of a semisimple algebraic group by a parabolic subgroup. Using methods from the theory of arithmetic groups, due in…

Number Theory · Mathematics 2021-07-27 Nicolas de Saxcé

We explain how the theory of sandwich cellular algebras can be seen as a version of cell theory for algebras. We apply this theory to many examples such as Hecke algebras, and various monoid and diagram algebras.

Representation Theory · Mathematics 2026-04-07 Daniel Tubbenhauer

This monograph studies the relations between two approaches using positive definite kernels: probabilistic methods using Gaussian processes, and non-probabilistic methods using reproducing kernel Hilbert spaces (RKHS). They are widely…

Machine Learning · Statistics 2025-06-24 Motonobu Kanagawa , Philipp Hennig , Dino Sejdinovic , Bharath K. Sriperumbudur
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