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We study the Kantorovich-Rubinstein transhipment problem when the difference between the source and the target is not anymore a balanced measure but belongs to a suitable subspace $X(\Omega)$ of first order distribution. A particular…

Optimization and Control · Mathematics 2013-12-20 Guy Bouchitté , Giuseppe Buttazzo , Luigi De Pascale

This paper deals with homogeneous function spaces of Besov-Sobolev type within the framework of tempered distributions in Euclidean $n$-space based on Gauss-Weierstrass semi-groups. Related Fourier-analytical descriptions are incorporated…

Functional Analysis · Mathematics 2016-03-08 Hans Triebel

In this work, we investigate Gaussian Processes indexed by multidimensional distributions. While directly constructing radial positive definite kernels based on the Wasserstein distance has been proven to be possible in the unidimensional…

In this paper we study the variance of the Euler totient function (normalized to $\varphi(n)/n$) in the integers $\mathbb{Z}$ and in the polynomial ring $\mathbb{F}_q[T]$ over a finite field $\mathbb{F}_q$. It turns out that in…

Number Theory · Mathematics 2017-06-14 Tom van Overbeeke

We provide rates of convergence in the central limit theorem in terms of projective criteria for adapted stationary sequences of centered random variables taking values in Banach spaces, with finite moment of order $p \in ]2,3]$ as soon as…

Probability · Mathematics 2025-02-21 Aurélie Bigot

Given a compact space $X$ and a commutative Banach algebra $A$, the character spaces of $A$-valued function algebras on $X$ are investigated. The class of natural $A$-valued function algebras, those whose characters can be described by…

Functional Analysis · Mathematics 2016-05-19 Mortaza Abtahi

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

We recapitulate the Bayesian formulation of neural network based classifiers and show that, while sampling from the posterior does indeed lead to better generalisation than is obtained by standard optimisation of the cost function, even…

Machine Learning · Statistics 2019-04-09 Robert J. N. Baldock , Nicola Marzari

Let $M$ be a von Neumann algebra and let $(N_t)_{t\in[0,T]}$ be an increasing family of abelian von Neumann subalgebras encoding a (classical) information flow. Fix a faithful normal state $\varphi_\rho$ and a filtration of normal…

Operator Algebras · Mathematics 2026-02-05 Tian Xin , Liang Aoqin

A study of the relation between a noetherian local domain with a given valuation and its associated graded ring with respect to the valuation, which in some cases is an esentially toric variety, possibly of infinite embedding dimension, but…

Commutative Algebra · Mathematics 2007-05-23 Bernard Teissier

This paper investigates a general regularization framework for unsupervised domain adaptation in vector-valued regression under the covariate shift assumption, utilizing vector-valued reproducing kernel Hilbert spaces (vRKHS). Covariate…

Statistics Theory · Mathematics 2026-01-30 Markus Holzleitner , Sergiy Pereverzyev , Sergei V. Pereverzyev , Vaibhav Silmana , S. Sivananthan

Probabilistic classifiers output a probability distribution on target classes rather than just a class prediction. Besides providing a clear separation of prediction and decision making, the main advantage of probabilistic models is their…

Machine Learning · Computer Science 2019-02-20 Juozas Vaicenavicius , David Widmann , Carl Andersson , Fredrik Lindsten , Jacob Roll , Thomas B. Schön

The images of Hermite and Laguerre Sobolev spaces under the Hermite and special Hermite semigroups (respectively) are characterised. These are used to characterise the Schwartz class of rapidly decreasing functions. The image of the space…

Functional Analysis · Mathematics 2007-10-19 R. Radha , S. Thangavelu

Suppose we are given two metric spaces and a family of continuous transformations from one to the other. Given a probability distribution on each of these two spaces - namely the source and the target measures - the Wasserstein alignment…

Probability · Mathematics 2025-03-11 Soumik Pal , Bodhisattva Sen , Ting-Kam Leonard Wong

In this article we prove martingale type pointwise convergence theorems pertaining to tensor product splines defined on $d$-dimensional Euclidean space ($d$ is a positive integer), where conditional expectations are replaced by their…

Probability · Mathematics 2023-12-20 Markus Passenbrunner

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

In this paper we prove that if $X $ is a Banach space, then for every lower semi-continuous bounded below function $f, $ there exists a $\left(\varphi_1, \varphi_2\right)-$convex function $g, $ with arbitrarily small norm, such that $f + g…

Functional Analysis · Mathematics 2016-10-20 Abdelhakim Maaden , Abdelkader Stouti

When concept shifts and sample scarcity are present in the target domain of interest, nonparametric regression learners often struggle to generalize effectively. The technique of transfer learning remedies these issues by leveraging data or…

Machine Learning · Statistics 2025-01-22 Haotian Lin , Matthew Reimherr

Topological strings on toric Calabi--Yau threefolds can be defined non-perturbatively in terms of a free Fermi gas of N particles. Using this approach, we propose a definition of quantum mirror curves as quantum distributions on phase…

High Energy Physics - Theory · Physics 2019-03-27 Marcos Marino , Szabolcs Zakany

Consider a nonlinear ill-posed operator equation $F(u)=y$ where $F$ is defined on a Banach space $X$. In general, for solving this equation numerically, a finite dimensional approximation of $X$ and an approximation of $F$ are required.…

Numerical Analysis · Mathematics 2015-05-18 C. Poeschl , E. Resmerita , O. Scherzer
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