Sketching with Spherical Designs for Noisy Data Fitting on Spheres
From MaRDI portal
Publication:6189173
DOI10.1137/22m1484377arXiv2303.04550WikidataQ129334732 ScholiaQ129334732MaRDI QIDQ6189173
Shao-Bo Lin, Di Wang, Ding-Xuan Zhou
Publication date: 8 February 2024
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2303.04550
Computing methodologies for image processing (68U10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical interpolation (65D05) Numerical integration (65D30) Computational aspects of data analysis and big data (68T09)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Optimal asymptotic bounds for spherical designs
- Wendland functions with increasing smoothness converge to a Gaussian
- On the computation of spherical designs by a new optimization approach based on fast spherical Fourier transforms
- Optimal rates for regularization of statistical inverse learning problems
- Numerical integration over spheres of arbitrary dimension
- Continuous and discrete least-squares approximation by radial basis functions on spheres
- A partition of the unit sphere into regions of equal area and small diameter
- A survey on spherical designs and algebraic combinatorics on spheres
- Stability results for scattered-data interpolation on Euclidean spheres
- Spherical codes and designs
- A new approach to the construction of optimal designs
- Radial basis function approximation of noisy scattered data on the sphere
- Approximation in rough native spaces by shifts of smooth kernels on spheres
- Approximation of smooth functions on compact two-point homogeneous spaces
- A distribution-free theory of nonparametric regression
- Well-separated spherical designs
- Distributing many points on spheres: minimal energy and designs
- Direct and inverse Sobolev error estimates for scattered data interpolation via spherical basis functions
- Spherical harmonics
- Shannon sampling. II: Connections to learning theory
- Spherical Marcinkiewicz-Zygmund inequalities and positive quadrature
- Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
- Regularized Least Squares Approximations on the Sphere Using Spherical Designs
- Kernel Approximation on Manifolds I: Bounding the Lebesgue Constant
- Multiscale Analysis in Sobolev Spaces on the Sphere
- Kernel Approximation on Manifolds II: The $L_{\infty}$ Norm of the $L_2$ Projector
- Multivariate Monte Carlo Approximation Based on Scattered Data
- Spline Interpolation and Smoothing on the Sphere
- Multivariate interpolation of large sets of scattered data
- Deep distributed convolutional neural networks: Universality
- A Novel Sampling Theorem on the Sphere
- Efficient Spherical Designs with Good Geometric Properties
- Spherical Designs and Nonconvex Minimization for Recovery of Sparse Signals on the Sphere
- Scattered Data Interpolation on Spheres: Error Estimates and Locally Supported Basis Functions
- Shannon sampling and function reconstruction from point values
- Covering a sphere and extremal properties of orthogonal polynomials
- Lasso Hyperinterpolation Over General Regions
- Analysis of regularized Nyström subsampling for regression functions of low smoothness
- Localized Linear Polynomial Operators and Quadrature Formulas on the Sphere
- Sparse Image Reconstruction on the Sphere: Implications of a New Sampling Theorem
- Existence of Solutions to Systems of Underdetermined Equations and Spherical Designs
- Distributed Filtered Hyperinterpolation for Noisy Data on the Sphere
- Introduction to nonparametric estimation
- How good can polynomial interpolation on the sphere be?
