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It is an open problem whether an infinite-dimensional amenable Banach algebra exists whose underlying Banach space is reflexive. We give sufficient conditions for a reflexive, amenable Banach algebra to be finite-dimensional (and thus a…

Functional Analysis · Mathematics 2007-05-23 Volker Runde

Traditionally, kernel methods rely on the representer theorem which states that the solution to a learning problem is obtained as a linear combination of the data mapped into the reproducing kernel Hilbert space (RKHS). While elegant from…

Machine Learning · Computer Science 2021-08-30 Riikka Huusari , Sahely Bhadra , Cécile Capponi , Hachem Kadri , Juho Rousu

The idea of best approximation in linear n-normed space is presented and some examples showing various possibilities of best approximations in linear n-normed space is given. Also, we study strictly convex n-norm and enquire about the…

Functional Analysis · Mathematics 2023-09-27 Prasenjit Ghosh , T. K. Samanta

In the study of locally convex quasi *-algebras an important role is played by representable linear functionals; i.e., functionals which allow a GNS-construction. This paper is mainly devoted to the study of the continuity of representable…

Functional Analysis · Mathematics 2017-06-14 Maria Stella Adamo , Camillo Trapani

In this note, we provide a characterization for the set of extreme points of the Lipschitz unit ball in a specific vectorial setting. While the analysis of the case of real-valued functions is covered extensively in the literature, no…

Functional Analysis · Mathematics 2025-10-24 Kristian Bredies , Jonathan Chirinos Rodriguez , Emanuele Naldi

The first representation theorem establishes a correspondence between positive, self-adjoint operators and closed, positive forms on Hilbert spaces. The aim of this paper is to show that some of the results remain true if the underlying…

Functional Analysis · Mathematics 2007-05-23 Balint Farkas , Mate Matolcsi

Given a category of objects, it is both useful and important to know if all the objects in the category may be realised as sub-objects -- via morphisms in the given category -- of a single object in that category enjoying some nice…

Functional Analysis · Mathematics 2019-07-18 M. A. Sofi

Motivated by the growing interest in representation learning approaches that uncover the latent structure of high-dimensional data, this work proposes new algorithms for reconstruction-based manifold learning within Reproducing-Kernel…

Machine Learning · Computer Science 2026-05-07 Enrique Feito-Casares , Francisco M. Melgarejo-Meseguer , José-Luis Rojo-Álvarez

We show that any bounded operator $T$ on a separable, reflexive, infinite-dimensional Banach space $X$ admits a rank one perturbation which has an invariant subspace of infinite dimension and codimension. In the non-reflexive spaces, we…

Functional Analysis · Mathematics 2012-08-30 Alexey I. Popov , Adi Tcaciuc

In this paper we solve support vector machines in reproducing kernel Banach spaces with reproducing kernels defined on nonsymmetric domains instead of the traditional methods in reproducing kernel Hilbert spaces. Using the orthogonality of…

Machine Learning · Statistics 2015-01-16 Gregory E. Fasshauer , Fred J. Hickernell , Qi Ye

It is proved that a commutative algebra $A$ of operators on a reflexive real Banach space has an invariant subspace if each operator $T\in A$ satisfies the condition $$\|1- \varepsilon T^2\|_e \le 1 + o(\varepsilon) \text{ when }…

Functional Analysis · Mathematics 2022-09-23 V. I. Lomonosov , V. S. Shulman

Motivated by a general dilation theory for operator-valued measures, framings and bounded linear maps on operator algebras, we consider the dilation theory of the above objects with special structures. We show that every operator-valued…

Functional Analysis · Mathematics 2014-11-18 Deguang Han , David R. Larson , Bei Liu , Rui Liu

A typical approach in estimating the learning rate of a regularized learning scheme is to bound the approximation error by the sum of the sampling error, the hypothesis error and the regularization error. Using a reproducing kernel space…

Machine Learning · Statistics 2011-01-28 Guohui Song , Haizhang Zhang

We present necessary and sufficient conditions to hold true a Kramer type sampling theorem over semi-inner product reproducing kernel Banach spaces. Under some sampling-type hypotheses over a sequence of functions on these Banach spaces it…

Functional Analysis · Mathematics 2018-07-09 Hernán D. Centeno , Juan M. Medina

In this paper it will be shown that assuming the Continuum Hypothesis (CH) every nonreflexive Banach space ultrapower is isometrically isomorphic to the space of continuous, bounded and real-valued functions on the Parovicenko space. This…

Logic · Mathematics 2011-07-11 Piotr Wilczek

Let X be a non-degenerate left Banach module over a normed algebra A having a bounded approximate left identity. We show that, if A is a left ideal of a larger algebra, then this representation can be extended to a representation of the…

Functional Analysis · Mathematics 2023-05-31 Sjoerd Dirksen , Marcel de Jeu , Marten Wortel

In this work we consider, in a Banach space framework, the regularization of linear ill-posed problems. Our focus is on the recovery of solutions that have a logarithmic source representation. Such cases typically occur in exponentially…

Numerical Analysis · Mathematics 2025-09-09 Robert Plato

We establish a general CCR (liminarity) property for uniformly bounded irreducible representations of nilpotent Lie groups on reflexive Banach spaces, extending the well known property of unitary irreducible representations of these groups…

Representation Theory · Mathematics 2019-05-09 Ingrid Beltita , Daniel Beltita , Jose E. Gale

We consider ill-posed linear operator equations with operators acting between Banach spaces. For solution approximation, the methods of choice here are projection methods onto finite dimensional subspaces, thus extending existing results…

Numerical Analysis · Mathematics 2016-04-26 Uno Hämarik , Barbara Kaltenbacher , Urve Kangro , Elena Resmerita

Probably the most important problem in machine learning is the preliminary biasing of a learner's hypothesis space so that it is small enough to ensure good generalisation from reasonable training sets, yet large enough that it contains a…

Machine Learning · Computer Science 2019-12-20 Jonathan Baxter