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The Rate of Convergence of Variation-Constrained Deep Neural Networks

The Rate of Convergence of Variation-Constrained Deep Neural Networks

22 June 2021
Gen Li
Jie Ding
ArXivPDFHTML

Papers citing "The Rate of Convergence of Variation-Constrained Deep Neural Networks"

5 / 5 papers shown
Title
Analysis of the rate of convergence of an over-parametrized
  convolutional neural network image classifier learned by gradient descent
Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned by gradient descent
Michael Kohler
A. Krzyżak
Benjamin Walter
36
1
0
13 May 2024
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO
  Regularization
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization
Geng Li
G. Wang
Jie Ding
34
3
0
07 May 2023
Analysis of the rate of convergence of an over-parametrized deep neural
  network estimate learned by gradient descent
Analysis of the rate of convergence of an over-parametrized deep neural network estimate learned by gradient descent
Michael Kohler
A. Krzyżak
32
10
0
04 Oct 2022
On the universal consistency of an over-parametrized deep neural network
  estimate learned by gradient descent
On the universal consistency of an over-parametrized deep neural network estimate learned by gradient descent
Selina Drews
Michael Kohler
30
13
0
30 Aug 2022
Norm-Based Capacity Control in Neural Networks
Norm-Based Capacity Control in Neural Networks
Behnam Neyshabur
Ryota Tomioka
Nathan Srebro
127
577
0
27 Feb 2015
1