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This paper studies the learning of linear operators between infinite-dimensional Hilbert spaces. The training data comprises pairs of random input vectors in a Hilbert space and their noisy images under an unknown self-adjoint linear…

Statistics Theory · Mathematics 2023-05-12 Maarten V. de Hoop , Nikola B. Kovachki , Nicholas H. Nelsen , Andrew M. Stuart

Singular numbers of operators between Hilbert spaces were generalized to Banach spaces by s-numbers (in the sense of Pietsch). This allows for different choices, including approximation, Gelfand, Kolmogorov and Bernstein numbers. Here, we…

Functional Analysis · Mathematics 2024-10-15 Mario Ullrich

For a bounded linear operator on a Banach space, we study approximation of the spectrum and pseudospectra in the Hausdorff distance. We give sufficient and necessary conditions in terms of pointwise convergence of appropriate spectral…

Functional Analysis · Mathematics 2022-09-12 Marko Lindner , Dennis Schmeckpeper

In this article, we present some new general forms of numerical radius inequalities for Hilbert space operators. The significance of these inequalities follow from the way they extend and refine some known results in this field. Among other…

Functional Analysis · Mathematics 2019-06-21 Mohammad Sababheh , Hamid Reza Moradi

We study two subspace systems in a separable infinite-dimensional Hilbert space up to (bounded) isomorphism. One of the main result of this paper is the following: Isomorphism classes of two subspace systems given by graphs of bounded…

Functional Analysis · Mathematics 2018-10-15 Masatoshi Enomoto , Yasuo Watatani

For a closed-loop control system with a digital channel between the sensor and the controller, the notion of invariance entropy quantifies the smallest average rate of information above which a given compact subset of the state space can be…

Optimization and Control · Mathematics 2021-11-19 Mahendra Singh Tomar , Christoph Kawan , Majid Zamani

We consider $\ell^r$ extensions of Calderon-Zygmund operators on weighted spaces $L^p(w)$ with $w$ an $A_p$ weight and $1 < p < \infty$. We give quantitative estimates of these operators' norm in terms of a given weight's $A_p$…

Classical Analysis and ODEs · Mathematics 2012-10-29 James Scurry

We give new necessary and sufficient conditions for the numerical range $W(T)$ of an operator $T \in \mathcal{B}(\mathcal{H})$ to be a subset of the closed elliptical set $K_\delta \subseteq \mathbb{C}$ given by \[ K_\delta {\stackrel{\rm…

Functional Analysis · Mathematics 2024-06-10 Jim Agler , Zinaida A. Lykova , N. J. Young

The asymptotic behavior for entropy numbers of general Fourier multiplier operators of multiple series with respect to an abstract complete orthonormal system $\{\phi_{\textbf{m}}\}_{\textbf{m}\in \mathbb{N}^d_0}$ on a probability space and…

Functional Analysis · Mathematics 2021-07-12 Sergio Andrés Córdoba Pareja , Jéssica Milaré , Sergio A. Tozoni

We study the relation between metric entropy and escape of mass for the Hilbert modular spaces with the action of a diagonal element.

Dynamical Systems · Mathematics 2011-11-29 Shirali Kadyrov

Mixture distributions are a workhorse model for multimodal data in information theory, signal processing, and machine learning. Yet even when each component density is simple, the differential entropy of the mixture is notoriously hard to…

Information Theory · Computer Science 2026-02-18 Namyoon Lee

The paper establishes error orders for integral limit approximations to the traces of products of Toeplitz matrices generated by integrable real symmetric functions defined on the unit circle. These approximations and the corresponding…

Probability · Mathematics 2014-05-15 M. S. Ginovyan , A. A. Sahakyan

We study the notion of approximate entropy within the framework of network theory. Approximate entropy is an uncertainty measure originally proposed in the context of dynamical systems and time series. We firstly define a purely structural…

Disordered Systems and Neural Networks · Physics 2013-05-30 James West , Lucas Lacasa , Simone Severini , Andrew Teschendorff

Let A be a matrix, c be any linear objective function and x be a fractional vector, say an LP solution to some discrete optimization problem. Then a recurring task in theoretical computer science (and in approximation algorithms in…

Data Structures and Algorithms · Computer Science 2011-04-26 Thomas Rothvoss

Let $A_{\alpha}^{p}(\mathbb{B}^n;\mathbb{C}^d)$ be the weighted Bergman space on the unit ball $\mathbb{B}^n$ of $\mathbb{C}^n$ of functions taking values in $\mathbb{C}^d$. For $1<p<\infty$ let $\mathcal{T}_{p,\alpha}$ be the algebra…

Classical Analysis and ODEs · Mathematics 2016-02-08 Robert S. Rahm , Brett D. Wick

In this paper, we present intriguing findings that characterize both the closed (unbounded) and bounded EP operators on Hilbert spaces. Additionally, we demonstrate the result $\gamma(T) \leq r(T)$, where $T$ is a bounded EP operator, and…

Functional Analysis · Mathematics 2024-12-10 Arup Majumdar , P. Sam Johnson

The main result of the paper shows that, for 1<p and 1<=q, a linear operator T from l_p to l_q attains its norm if, and only if, there exists a not weakly null maximizing sequence for T (counterexamples can be easily constructed when p=1).…

Functional Analysis · Mathematics 2015-10-02 Daniel Pellegrino , Eduardo V. Teixeira

We calculate the entanglement entropy between two (maximally-extended) spacetime regions of static black hole, seperated by horizon. As a first case, we consider the Schwarzschild black hole, and then we extend the calculations to the…

General Relativity and Quantum Cosmology · Physics 2023-03-15 Hadyan Luthfan Prihadi , Freddy Permana Zen , Seramika Ariwahjoedi , Donny Dwiputra

Maximum entropy models are increasingly being used to describe the collective activity of neural populations with measured mean neural activities and pairwise correlations, but the full space of probability distributions consistent with…

Biological Physics · Physics 2017-08-22 Badr F. Albanna , Christopher Hillar , Jascha Sohl-Dickstein , Michael R. DeWeese

In this note we study the problem of sampling and reconstructing signals which are assumed to lie on or close to one of several subspaces of a Hilbert space. Importantly, we here consider a very general setting in which we allow infinitely…

Information Theory · Computer Science 2009-12-02 Thomas Blumensath