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In this chapter we provide a theoretically founded investigation of state-of-the-art learning approaches for inverse problems from the point of view of spectral reconstruction operators. We give an extended definition of regularization…

Numerical Analysis · Mathematics 2024-06-05 Martin Burger , Samira Kabri

The Bernstein approximation problem is to determine whether or not the space of all polynomials is dense in a given weighted $C_0$-space on the real line. A theorem of L. de Branges characterizes non--density by existence of an entire…

Complex Variables · Mathematics 2012-07-24 Anton Baranov , Harald Woracek

Conditional stability estimates allow us to characterize the degree of ill-posedness of many inverse problems, but without further assumptions they are not sufficient for the stable solution in the presence of data perturbations. We here…

Numerical Analysis · Mathematics 2018-10-17 Herbert Egger , Bernd Hofmann

Motivated by the success of Sinkhorn's algorithm for entropic optimal transport, we study convergence properties of iterative proportional fitting procedures (IPFP) used to solve more general information projection problems. We establish…

Optimization and Control · Mathematics 2025-04-14 Stephan Eckstein , Aziz Lakhal

We consider the problem of reconstructing the shape of an impenetrable sound-soft obstacle from scattering measurements. The input data is assumed to be the far-field pattern generated when a plane wave impinges on an unknown obstacle from…

Numerical Analysis · Mathematics 2015-05-28 Carlos Borges , Leslie Greengard

In [18] Fournier and Printems establish a methodology which allows to prove the absolute continuity of the law of the solution of some stochastic equations with H\"{o}lder continuous coefficients. This is of course out of reach by using…

Probability · Mathematics 2017-04-03 V. Bally , L. Caramellino

A number of regularization methods for discrete inverse problems consist in considering weighted versions of the usual least square solution. However, these so-called filter methods are generally restricted to monotonic transformations,…

Statistics Theory · Mathematics 2011-05-05 Paul Rochet

This paper discusses a generalization of spectral representations related to convex one-homogeneous regularization functionals, e.g. total variation or $\ell^1$-norms. Those functionals serve as a substitute for a Hilbert space structure…

Numerical Analysis · Mathematics 2015-03-19 Martin Burger , Lina Eckardt , Guy Gilboa , Michael Moeller

The purpose of this paper is to expose and investigate natural phase-space formulations of two longstanding problems in the restriction theory of the Fourier transform. These problems, often referred to as the Stein and Mizohata--Takeuchi…

Classical Analysis and ODEs · Mathematics 2025-10-07 Jonathan Bennett , Susana Gutierrez , Shohei Nakamura , Itamar Oliveira

In a common formulation of semi-infinite programs, the infinite constraint set is a requirement that a function parametrized by the decision variables is nonnegative over an interval. If this function is sufficiently closely approximable by…

Optimization and Control · Mathematics 2017-03-24 Dávid Papp

Several problems on Fourier series and trigonometric approximation on a hexagon and a triangle are studied. The results include Abel and Ces\`aro summability of Fourier series, degree of approximation and best approximation by trigonometric…

Classical Analysis and ODEs · Mathematics 2008-02-05 Yuan Xu

In this work, we consider the linear inverse problem $y=Ax+\epsilon$, where $A\colon X\to Y$ is a known linear operator between the separable Hilbert spaces $X$ and $Y$, $x$ is a random variable in $X$ and $\epsilon$ is a zero-mean random…

Machine Learning · Statistics 2021-11-23 Giovanni S. Alberti , Ernesto De Vito , Matti Lassas , Luca Ratti , Matteo Santacesaria

We consider interpolation inequalities for imbeddings of the $l^2$-sequence spaces over $d$-dimensional lattices into the $l^\infty_0$ spaces written as interpolation inequality between the $l^2$-norm of a sequence and its difference. A…

Analysis of PDEs · Mathematics 2014-07-03 Alexei Ilyin , Ari Laptev , Sergey Zelik

This work is concerned with linear inverse problems where a distributed parameter is known a priori to only take on values from a given discrete set. This property can be promoted in Tikhonov regularization with the aid of a suitable convex…

Optimization and Control · Mathematics 2018-04-19 Christian Clason , Thi Bich Tram Do

In this short note, we formulate the convergence rates of the well known Tikhonov regularization scheme for solving the nonlinear ill-posed problems in Banach spaces. For deriving the convergence rates, we employ the novel smoothness…

Numerical Analysis · Mathematics 2022-11-30 Gaurav Mittal , Ankik Kumar Giri

We firstly describe a maximal inequality for dual Sobolev spaces W^{-1,p}. This one corresponds to a "Sobolev version" of usual properties of the Hardy-Littlewood maximal operator in Lebesgue spaces. Even in the euclidean space, this one…

Functional Analysis · Mathematics 2008-12-17 Frederic Bernicot

The relationship between the operator norms of fractional integral operators acting on weighted Lebesgue spaces and the constant of the weights is investigated. Sharp boundsare obtained for both the fractional integral operators and the…

Classical Analysis and ODEs · Mathematics 2012-05-08 Michael Lacey , Kabe Moen , Carlos Perez , Rodolfo H. Torres

We solve the inverse problems to recover Dirac systems on an interval or semiaxis from their spectral functions (matrix valued functions) for the case of locally square-integrable potentials. Direct problems in terms of spectral functions…

Spectral Theory · Mathematics 2026-04-29 Alexander Sakhnovich

In this paper we deal with linear inverse problems and convergence rates for Tikhonov regularization. We consider regularization in a scale of Banach spaces, namely the scale of Besov spaces. We show that regularization in Banach scales…

Functional Analysis · Mathematics 2009-11-13 Dirk Lorenz , Dennis Trede

In this work we introduce a new measure for the dispersion of the spectral scale of a Hermitian (self-adjoint) operator acting on a separable infinite dimensional Hilbert space that we call spectral spread. Then, we obtain some…

Functional Analysis · Mathematics 2022-10-18 Pedro Massey , Demetrio Stojanoff , Sebastian Zarate