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Due to their flexibility, frames of Hilbert spaces are attractive alternatives to bases in approximation schemes for problems where identifying a basis is not straightforward or even feasible. Computing a best approximation using frames,…

Numerical Analysis · Mathematics 2020-07-08 Ben Adcock , Mohsen Seifi

A simple formal recasting of well known arguments concerning the ordering problems of General Relativity allows to obtain in such a context a Gr\"{o}enewald Van Hove like theorem.

Mathematical Physics · Physics 2007-05-23 Gavriel Segre

This paper presents a general coding method where data in a Hilbert space are represented by finite dimensional coding vectors. The method is based on empirical risk minimization within a certain class of linear operators, which map the set…

Machine Learning · Statistics 2011-09-05 Andreas Maurer Massimiliano Pontil

Given a Hilbert space $\mathcal H$ and a finite measure space $\Omega$, the approximation of a vector-valued function $f: \Omega \to \mathcal H$ by a $k$-dimensional subspace $\mathcal U \subset \mathcal H$ plays an important role in…

Numerical Analysis · Mathematics 2024-08-07 Daniel Kressner , Tingting Ni , André Uschmajew

A large literature specifies conditions under which the information complexity for a sequence of numerical problems defined for dimensions $1, 2, \ldots$ grows at a moderate rate, i.e., the sequence of problems is tractable. Here, we focus…

Numerical Analysis · Mathematics 2024-04-24 Onyekachi Emenike , Fred J. Hickernell , Peter Kritzer

We develop the theory of Wigner representations for general probabilistic theories (GPTs), a large class of operational theories that include both classical and quantum theory. The Wigner representations that we introduce are a natural way…

Quantum Physics · Physics 2025-02-11 Ties-A. Ohst , Martin Plávala

We consider general difference equations $u_{n+1} = F(u)_n$ for $n \in \mathbb{Z}$ on exponentially weighted $\ell_2$ spaces of two-sided Hilbert space valued sequences $u$ and discuss initial value problems. As an application of the…

Dynamical Systems · Mathematics 2018-10-05 Konrad Kitzing , Rainer Picard , Stefan Siegmund , Sascha Trostorff , Marcus Waurick

Starting categorically, we give simple and precise models of equivariant classifying spaces. We need these models for work in progress in equivariant infinite loop space theory and equivariant algebraic K-theory, but the models are of…

Algebraic Topology · Mathematics 2018-03-16 B. J. Guillou , J. P. May , M. Merling

The Hilbert metric on convex subsets of $\mathbb R^n$ has proven a rich notion and has been extensively studied. We propose here a generalization of this metric to subset of complex projective spaces and give examples of applications to…

Metric Geometry · Mathematics 2022-03-25 Elisha Falbel , Antonin Guilloux , Pierre Will

This paper is a continuation of work arXiv:2006.09583 devoted to establishment of the convergence rate in the strong invariance principle for cumulative processes. We establish optimal rate of convergence for the case when regeneration…

Probability · Mathematics 2020-07-31 Elena Bashtova , Alexey Shashkin

Wiener's criterion for the regularity of a boundary point with respect to the Dirichlet problem for the Laplace equation has been extended to various classes of elliptic and parabolic partial differential equations. They include linear…

Analysis of PDEs · Mathematics 2007-05-23 Vladimir Maz'ya

We study the convergence of type I Hermite-Pad\'e approximation for a class of meromorphic functions obtained by adding a vector of rational functions with real coefficients to a Nikishin system of functions.

Complex Variables · Mathematics 2014-06-17 G. López Lagomasino , S. Medina Peralta

This work deals with embeddings, of any integer order, for generalized Lorentz-Zygmund-Sobolev spaces on Euclidean domains satisfying minimal regularity assumptions. Explicit rearrangement-invariant, H\"older, Morrey and Campanato optimal…

Functional Analysis · Mathematics 2026-05-25 Paola Cavaliere , Ladislav Drážný

The Computation of discrete Contractive semigroups becomes necessary when we deal with several types of evolution equations in Discretizable Hilbert spaces, in this work we study some properties of the discrete forms of the contractive…

Numerical Analysis · Mathematics 2010-12-24 Fredy Vides

Functional linear regression is one of the fundamental and well-studied methods in functional data analysis. In this work, we investigate the functional linear regression model within the context of reproducing kernel Hilbert space by…

Statistics Theory · Mathematics 2024-12-12 Naveen Gupta , S. Sivananthan , Bharath K. Sriperumbudur

This review presents an overview of various kinds of models -- physical, abstract, mathematical, visual -- that can be used to present the concepts and applications of Einstein's general theory of relativity at the level of undergraduate…

General Relativity and Quantum Cosmology · Physics 2019-01-01 Markus Pössel

Locally optimal designs for generalized linear models are derived at certain values of the regression parameters. In the present paper a general setup of the generalized linear model is considered. Analytic solutions for optimal designs are…

Statistics Theory · Mathematics 2019-06-06 Osama Idais

We study the best approximation and distance problems in the operator space $\B(\HS)$ and in the space of trace class operators $\LS^1(\B(\HS))$. Formulations of distances are obtained in both cases. The case of finite-dimensional…

Functional Analysis · Mathematics 2025-05-20 Saikat Roy

We prove a localization formula for virtual fundamental classes in the context of torus equivariant perfect obstruction theories. As an application, the higher genus Gromov-Witten invariants of projective space are expressed as graph sums…

alg-geom · Mathematics 2008-02-03 T. Graber , R. Pandharipande

We study the problem of binary classification from the point of view of learning convex polyhedra in Hilbert spaces, to which one can reduce any binary classification problem. The problem of learning convex polyhedra in finite-dimensional…

Machine Learning · Computer Science 2023-03-06 Sergei Chubanov