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Dimension independent bounds for general shallow networks
v1v2 (latest)

Dimension independent bounds for general shallow networks

Neural Networks (NN), 2019
26 August 2019
H. Mhaskar
ArXiv (abs)PDFHTML

Papers citing "Dimension independent bounds for general shallow networks"

12 / 12 papers shown
Learning on manifolds without manifold learning
Learning on manifolds without manifold learning
H. Mhaskar
Ryan O'Dowd
267
7
0
20 Feb 2024
Tractability of approximation by general shallow networks
Tractability of approximation by general shallow networksAnalysis and Applications (AA), 2023
H. Mhaskar
Tong Mao
182
6
0
07 Aug 2023
Weighted variation spaces and approximation by shallow ReLU networks
Weighted variation spaces and approximation by shallow ReLU networksApplied and Computational Harmonic Analysis (ACHA), 2023
Ronald A. DeVore
Robert D. Nowak
Rahul Parhi
Jonathan W. Siegel
272
8
0
28 Jul 2023
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural NetworksConstructive approximation (Constr. Approx.), 2023
Jonathan W. Siegel
630
17
0
28 Jul 2023
Rates of Approximation by ReLU Shallow Neural Networks
Rates of Approximation by ReLU Shallow Neural NetworksJournal of Complexity (J. Complexity), 2023
Tong Mao
Ding-Xuan Zhou
246
39
0
24 Jul 2023
Nonparametric regression using over-parameterized shallow ReLU neural
  networks
Nonparametric regression using over-parameterized shallow ReLU neural networksJournal of machine learning research (JMLR), 2023
Yunfei Yang
Ding-Xuan Zhou
381
18
0
14 Jun 2023
Approximation by non-symmetric networks for cross-domain learning
Approximation by non-symmetric networks for cross-domain learningNeural Networks (Neural Netw.), 2023
H. Mhaskar
341
1
0
06 May 2023
A low discrepancy sequence on graphs
A low discrepancy sequence on graphsJournal of Fourier Analysis and Applications (JFAA), 2020
A. Cloninger
H. Mhaskar
285
4
0
08 Oct 2020
A deep network construction that adapts to intrinsic dimensionality
  beyond the domain
A deep network construction that adapts to intrinsic dimensionality beyond the domain
A. Cloninger
T. Klock
AI4CE
409
14
0
06 Aug 2020
Banach Space Representer Theorems for Neural Networks and Ridge Splines
Banach Space Representer Theorems for Neural Networks and Ridge Splines
Rahul Parhi
Robert D. Nowak
270
7
0
10 Jun 2020
Kernel based analysis of massive data
Kernel based analysis of massive dataFrontiers in Applied Mathematics and Statistics (FAMS), 2020
H. Mhaskar
246
16
0
30 Mar 2020
Function approximation by deep networks
Function approximation by deep networksCommunications on Pure and Applied Analysis (CPAA), 2019
H. Mhaskar
T. Poggio
211
25
0
30 May 2019
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