Infinite-Variate $L^2$-Approximation with Nested Subspace Sampling
Fuente:
arXiv
Saved in:
| Main Authors: | Harsha, Kumar, Gnewuch, Michael, Wnuk, Marcin |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Data Compression using Rank-1 Lattices for Parameter Estimation in Machine Learning
by: Gnewuch, Michael, et al.
Published: (2024)
by: Gnewuch, Michael, et al.
Published: (2024)
Infinite-dimensional integration and $L^2$-approximation on Hermite spaces
by: Gnewuch, Michael, et al.
Published: (2023)
by: Gnewuch, Michael, et al.
Published: (2023)
Multi- and Infinite-variate Integration and $L^2$-Approximation on Hilbert Spaces with Gaussian Kernels
by: Gnewuch, Michael, et al.
Published: (2024)
by: Gnewuch, Michael, et al.
Published: (2024)
New Bounds for the Extreme and the Star Discrepancy of Double-Infinite Matrices
by: Fiedler, Jasmin, et al.
Published: (2023)
by: Fiedler, Jasmin, et al.
Published: (2023)
Embeddings of Reproducing Kernel Hilbert Spaces with General Weights
by: Gnewuch, Michael, et al.
Published: (2026)
by: Gnewuch, Michael, et al.
Published: (2026)
Adaptive and non-adaptive randomized approximation of high-dimensional vectors
by: Kunsch, Robert J., et al.
Published: (2024)
by: Kunsch, Robert J., et al.
Published: (2024)
Uniform approximation of vectors using adaptive randomized information
by: Kunsch, Robert J., et al.
Published: (2024)
by: Kunsch, Robert J., et al.
Published: (2024)
Computable error bounds for quasi-Monte Carlo using points with non-negative local discrepancy
by: Gnewuch, Michael, et al.
Published: (2023)
by: Gnewuch, Michael, et al.
Published: (2023)
Subspace Diffusion Posterior Sampling for Travel-Time Tomography
by: Cao, Xiang, et al.
Published: (2024)
by: Cao, Xiang, et al.
Published: (2024)
Randomized approximation of summable sequences -- adaptive and non-adaptive
by: Kunsch, Robert, et al.
Published: (2023)
by: Kunsch, Robert, et al.
Published: (2023)
QRP Variation of Cross--Approximation Iterations for Low Rank Approximation
by: Pan, Victor Y., et al.
Published: (2018)
by: Pan, Victor Y., et al.
Published: (2018)
A Dynamic Subspace Approach for Low-rank Approximation of Large-scale Nonlinear Systems
by: DeChant, Jack, et al.
Published: (2026)
by: DeChant, Jack, et al.
Published: (2026)
Hybrid Stochastic Functional Differential Equations with Infinite Delay: Approximations and Numerics
by: Li, Guozhen, et al.
Published: (2025)
by: Li, Guozhen, et al.
Published: (2025)
Operator SVD with Neural Networks via Nested Low-Rank Approximation
by: Ryu, J. Jon, et al.
Published: (2024)
by: Ryu, J. Jon, et al.
Published: (2024)
Stability of Least Squares Approximation under Random Sampling
by: Xu, Zhiqiang, et al.
Published: (2024)
by: Xu, Zhiqiang, et al.
Published: (2024)
Exploring Chebyshev Polynomial Approximations: Error Estimates for Functions of Bounded Variation
by: Akansha, S
Published: (2024)
by: Akansha, S
Published: (2024)
Nested Bregman Iterations for Decomposition Problems
by: Wolf, Tobias, et al.
Published: (2024)
by: Wolf, Tobias, et al.
Published: (2024)
Subspace decomposition with defect diffusion coefficient
by: Kolombage, Dilini, et al.
Published: (2026)
by: Kolombage, Dilini, et al.
Published: (2026)
A Novel Transformed Fibered Rank Approximation with Total Variation Regularization for Tensor Completion
by: Chen, Ziming, et al.
Published: (2025)
by: Chen, Ziming, et al.
Published: (2025)
Stable Mesh-Free Variational Radial Basis Function Approximation for Elliptic PDEs and Obstacle Problems
by: Le, Tan Phuong Dong, et al.
Published: (2026)
by: Le, Tan Phuong Dong, et al.
Published: (2026)
Deep neural network approximation for high-dimensional parabolic partial integro-differential equations
by: Baranek, Marcin
Published: (2025)
by: Baranek, Marcin
Published: (2025)
$L^p$ Estimates for Numerical Approximation of Hamilton-Jacobi Equations
by: Basti, Alessio, et al.
Published: (2025)
by: Basti, Alessio, et al.
Published: (2025)
Error Estimates for Discontinuous Galerkin Approximations to the Vlasov-Unsteady Stokes System
by: Hutridurga, Harsha, et al.
Published: (2024)
by: Hutridurga, Harsha, et al.
Published: (2024)
Nested Multilevel Monte Carlo with Preintegration for Efficient Risk Estimation
by: Xu, Yu, et al.
Published: (2026)
by: Xu, Yu, et al.
Published: (2026)
Approximating the Perfect Sampling Grids for Computing the Eigenvalues of Toeplitz-like Matrices Using the Spectral Symbol
by: Ekström, Sven-Erik
Published: (2019)
by: Ekström, Sven-Erik
Published: (2019)
Numerical Approximation In Real Domain Of Special Function Of Product Of A Variable And Its Double Exponential
by: Wadhawan, Narinder Kumar
Published: (2025)
by: Wadhawan, Narinder Kumar
Published: (2025)
A Gradually Reinforced Sample-Average-Approximation Differentiable Homotopy Method for a System of Stochastic Equations
by: Li, Peixuan, et al.
Published: (2024)
by: Li, Peixuan, et al.
Published: (2024)
Subspace Splitting Fast Sampling from Gaussian Posterior Distributions of Linear Inverse Problems
by: Calvetti, Daniela, et al.
Published: (2025)
by: Calvetti, Daniela, et al.
Published: (2025)
Subspace embedding with random Khatri-Rao products and its application to eigensolvers
by: Bujanović, Zvonimir, et al.
Published: (2024)
by: Bujanović, Zvonimir, et al.
Published: (2024)
Subspace method based on neural networks for solving the partial differential equation
by: Xu, Zhaodong, et al.
Published: (2024)
by: Xu, Zhaodong, et al.
Published: (2024)
Locally Subspace-Informed Neural Operators for Efficient Multiscale PDE Solving
by: Rudikov, Alexander, et al.
Published: (2025)
by: Rudikov, Alexander, et al.
Published: (2025)
Sparsity for Infinite-Parametric Holomorphic Functions on Gaussian Spaces
by: Marcati, Carlo, et al.
Published: (2025)
by: Marcati, Carlo, et al.
Published: (2025)
An Approximation Theory Framework for Measure-Transport Sampling Algorithms
by: Baptista, Ricardo, et al.
Published: (2023)
by: Baptista, Ricardo, et al.
Published: (2023)
Structured Variational $D$-Decomposition for Accurate and Stable Low-Rank Approximation
by: Katende, Ronald
Published: (2025)
by: Katende, Ronald
Published: (2025)
StPINNs - Deep learning framework for approximation of stochastic differential equations
by: Baranek, Marcin, et al.
Published: (2025)
by: Baranek, Marcin, et al.
Published: (2025)
CUR Low Rank Approximation of a Matrix at Sublinear Cost
by: Go, Soo, et al.
Published: (2019)
by: Go, Soo, et al.
Published: (2019)
Deep Learning for Subspace Regression
by: Fanaskov, Vladimir, et al.
Published: (2025)
by: Fanaskov, Vladimir, et al.
Published: (2025)
PASE: A Massively Parallel Augmented Subspace Eigensolver for Large Scale Eigenvalue Problems
by: Liao, Yangfei, et al.
Published: (2025)
by: Liao, Yangfei, et al.
Published: (2025)
Subspace method based on neural networks for solving the partial differential equation in weak form
by: Liu, Pengyuan, et al.
Published: (2024)
by: Liu, Pengyuan, et al.
Published: (2024)
Variational derivation and compatible discretizations of the Maxwell-GLM system
by: Dumbser, Michael, et al.
Published: (2024)
by: Dumbser, Michael, et al.
Published: (2024)
Similar Items
-
Data Compression using Rank-1 Lattices for Parameter Estimation in Machine Learning
by: Gnewuch, Michael, et al.
Published: (2024) -
Infinite-dimensional integration and $L^2$-approximation on Hermite spaces
by: Gnewuch, Michael, et al.
Published: (2023) -
Multi- and Infinite-variate Integration and $L^2$-Approximation on Hilbert Spaces with Gaussian Kernels
by: Gnewuch, Michael, et al.
Published: (2024) -
New Bounds for the Extreme and the Star Discrepancy of Double-Infinite Matrices
by: Fiedler, Jasmin, et al.
Published: (2023) -
Embeddings of Reproducing Kernel Hilbert Spaces with General Weights
by: Gnewuch, Michael, et al.
Published: (2026)