Relevant sampling in a reproducing kernel subspace of Orlicz space

Spaces of measurable functions ((L^p)-spaces, Orlicz spaces, Köthe function spaces, Lorentz spaces, rearrangement invariant spaces, ideal spaces, etc.) (46E30) Probabilistic methods in Banach space theory (46B09) Inequalities for sums, series and integrals (26D15) Sampling theory in information and communication theory (94A20) Kernel operators (47B34)

Cites Work

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An optimal result for sampling density in shift-invariant spaces generated by Meyer scaling function
Random sampling of bandlimited functions
Relevant sampling in finitely generated shift-invariant spaces
Foundations of symmetric spaces of measurable functions. Lorentz, Marcinkiewicz and Orlicz spaces
The collected works of Arne Beurling. Volume 1: Complex analysis. Volume 2: Harmonic analysis. Ed. by Lennart Carleson, Paul Malliavin, John Neuberger, John Wermer
Some remarks on Stein's \(L \log L\) result
Sampling theorems for shift-invariant spaces, Gabor frames, and totally positive functions
Fourier frames
Beurling-Landau-type theorems for non-uniform sampling in shift invariant spline spaces
Random sampling and reconstruction of concentrated signals in a reproducing kernel space
Marcinkiewicz sampling theorem for Orlicz spaces
Complete interpolating sequences for the Gaussian shift-invariant space
Random sampling in reproducing kernel subspaces of \(L^p(\mathbb{R}^n)\)
Sampling and reconstruction of signals in a reproducing kernel subspace of \(L^p(\mathbb R^d)\)
Relevant sampling of band-limited functions
Necessary density conditions for sampling an interpolation of certain entire functions
Nonuniform sampling in principal shift-invariant subspaces of mixed Lebesgue spaces \(L^{p, q}(\mathbb{R}^{d + 1})\)
On the mathematical foundations of learning
Nonuniform Sampling and Reconstruction in Shift-Invariant Spaces
Deep vs. shallow networks: An approximation theory perspective
Convolution sampling and reconstruction of signals in a reproducing kernel subspace
On Hardy - Littlewood Maximal Functions in Orlicz Spaces
Functions with Disconnected Spectrum
Some remarks on Orlicz's interpolation theorem
Learning Theory
Sampling Theory for not Necessarily Band-Limited Functions: A Historical Overview
Deep distributed convolutional neural networks: Universality
Compressed Sensing of Analog Signals in Shift-Invariant Spaces
Monte Carlo Non-Local Means: Random Sampling for Large-Scale Image Filtering
Sampling-50 years after Shannon
Random Sampling of Multivariate Trigonometric Polynomials
A machine learning approach to optimal Tikhonov regularization I: Affine manifolds
Weighted random sampling and reconstruction in general multivariate trigonometric polynomial spaces
Random sampling and reconstruction in multiply generated shift-invariant spaces
Note on the class LlogL
Some notes on an expansion theorem of Paley and Wiener
Approximating functions with multi-features by deep convolutional neural networks
Spline representation and redundancies of one-dimensional ReLU neural network models
Random sampling of signals concentrated on compact set in localized reproducing kernel subspace of \(L^p (\mathbb{R}^n)\)
Random average sampling in a reproducing kernel subspace of mixed Lebesgue space \(L^{p,q}(\mathbb{R}^{n+1})\)
Error analysis of classification learning algorithms based on LUMs loss
Random sampling and reconstruction in reproducing kernel subspace of mixed Lebesgue spaces

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