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We develop the diffeomorphism invariant Colombeau-type algebra of nonlinear generalized functions in a modern and compact way. Using a unifying formalism for the local setting and on manifolds, the construction becomes simpler and more…

Functional Analysis · Mathematics 2013-03-14 Eduard Nigsch

We study invariance properties of Colombeau generalized functions under actions of smooth Lie transformation groups. Several characterization results analogous to the smooth setting are derived and applications to generalized rotational…

Functional Analysis · Mathematics 2007-05-23 Sanja Konjik , Michael Kunzinger

This contribution is the first in a series of three: it reports on the construction of (a fine sheaf of) diffeomorphism invariant Colombeau algebras on open sets of Eucildean space, which completes earlier approaches. Part II and III will…

Functional Analysis · Mathematics 2007-05-23 Roland Steinbauer

We investigate density of various subalgebras of regular generalized functions in the special Colombeau algebra of generalized functions.

Functional Analysis · Mathematics 2017-05-24 Hans Vernaeve

We introduce a theory of local kernels, which generalize the kernels used in the standard diffusion maps construction of nonparametric modeling. We prove that evaluating a local kernel on a data set gives a discrete representation of the…

Classical Analysis and ODEs · Mathematics 2015-01-07 Tyrus Berry , Timothy Sauer

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

The Colombeau algebra of generalized functions allows to unrestrictedly carry out products of distributions. We analyze this operation from a microlocal point of view, deriving a general inclusion relation for wave front sets of products in…

Functional Analysis · Mathematics 2007-05-23 Guenther Hoermann , Michael Kunzinger

We construct a diffeomorphism invariant (Colombeau-type) differential algebra canonically containing the space of distributions in the sense of L. Schwartz. Employing differential calculus in infinite dimensional (convenient) vector spaces,…

Functional Analysis · Mathematics 2007-05-23 Eva Farkas , Michael Grosser , Michael Kunzinger , Roland Steinbauer

We consider distributions on a closed compact manifold $M$ as maps on smoothing operators. Thus spaces of certain maps between $\Psi^{-\infty}(M)\to \mathcal{C}^{\infty}(M)$ are considered as generalized functions. For any collection of…

Analysis of PDEs · Mathematics 2009-06-09 Shantanu Dave

Invariance to nuisance transformations is one of the desirable properties of effective representations. We consider transformations that form a \emph{group} and propose an approach based on kernel methods to derive local group invariant…

Machine Learning · Computer Science 2017-05-25 Anant Raj , Abhishek Kumar , Youssef Mroueh , P. Thomas Fletcher , Bernhard Schölkopf

We introduce full diffeomorphism-invariant Colombeau algebras with added $\varepsilone$-dependence in the basic space. This unites the full and special settings of the theory into one single framework. Using locality conditions we find the…

Functional Analysis · Mathematics 2016-11-21 Eduard A. Nigsch , Michael Grosser

We discuss the nature of structure-preserving maps of varies function algebras. In particular, we identify isomorphisms between special Colombeau algebras on manifolds with invertible manifold-valued generalized functions in the case of…

Functional Analysis · Mathematics 2012-05-31 Annegret Burtscher

We give an overview of the development of algebras of generalized functions in the sense of Colombeau and recent advances concerning diffeomorphism invariant global algebras of generalized functions and tensor fields. We furthermore provide…

Functional Analysis · Mathematics 2014-07-01 Eduard A. Nigsch , Clemens Sämann

We develop a wavelet like representation of functions in $L^p(\mathbb{R})$ based on their Fourier--Hermite coefficients; i.e., we describe an expansion of such functions where the local behavior of the terms characterize completely the…

Classical Analysis and ODEs · Mathematics 2016-08-08 H. N. Mhaskar

We present a construction of algebras of generalized functions of Colombeau-type which, instead of asymptotic estimates with respect to a regularization parameter, employs only topological estimates on certain spaces of kernels for its…

Functional Analysis · Mathematics 2017-04-27 Eduard A. Nigsch

This paper gives a comprehensive analysis of algebras of Colombeau-type generalized functions in the range between the diffeomorphism-invariant quotient algebra $\mathcal{G}^d = \mathcal{E}_M/\mathcal{N}$ introduced in part I and…

Functional Analysis · Mathematics 2007-05-23 Michael Grosser

Positive definite kernels and their associated Reproducing Kernel Hilbert Spaces provide a mathematically compelling and practically competitive framework for learning from data. In this paper we take the approximation theory point of view…

Machine Learning · Computer Science 2018-08-06 Mikhail Belkin

This article is devoted to developing a theory for effective kernel interpolation and approximation in a general setting. For a wide class of compact, connected $C^\infty$ Riemannian manifolds, including the important cases of spheres and…

Classical Analysis and ODEs · Mathematics 2015-03-17 T. Hangelbroek , F. J. Narcowich , J. D. Ward

Summarizing basic facts from abstract topological modules over Colombeau generalized complex numbers we discuss duality of Colombeau algebras. In particular, we focus on generalized delta functionals and operator kernels as elements of dual…

Functional Analysis · Mathematics 2007-05-23 Claudia Garetto , Guenther Hoermann

Random feature approximation is arguably one of the most popular techniques to speed up kernel methods in large scale algorithms and provides a theoretical approach to the analysis of deep neural networks. We analyze generalization…

Machine Learning · Computer Science 2023-08-30 Mike Nguyen , Nicole Mücke
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