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A general approximation lower bound in $L^p$ norm, with applications to
  feed-forward neural networks
v1v2 (latest)

A general approximation lower bound in LpL^pLp norm, with applications to feed-forward neural networks

9 June 2022
El Mehdi Achour
Armand Foucault
Sébastien Gerchinovitz
Franccois Malgouyres
ArXiv (abs)PDFHTML

Papers citing "A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks"

14 / 14 papers shown
Title
Optimal learning of high-dimensional classification problems using deep
  neural networks
Optimal learning of high-dimensional classification problems using deep neural networks
P. Petersen
F. Voigtlaender
60
10
0
23 Dec 2021
VC dimension of partially quantized neural networks in the
  overparametrized regime
VC dimension of partially quantized neural networks in the overparametrized regime
Yutong Wang
Clayton D. Scott
76
1
0
06 Oct 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Zuowei Shen
Haizhao Yang
Shijun Zhang
157
118
0
28 Feb 2021
Sharp Bounds on the Approximation Rates, Metric Entropy, and $n$-widths
  of Shallow Neural Networks
Sharp Bounds on the Approximation Rates, Metric Entropy, and nnn-widths of Shallow Neural Networks
Jonathan W. Siegel
Jinchao Xu
123
87
0
29 Jan 2021
The phase diagram of approximation rates for deep neural networks
The phase diagram of approximation rates for deep neural networks
Dmitry Yarotsky
Anton Zhevnerchuk
62
121
0
22 Jun 2019
Universal Approximation with Deep Narrow Networks
Universal Approximation with Deep Narrow Networks
Patrick Kidger
Terry Lyons
130
333
0
21 May 2019
Optimal approximation of continuous functions by very deep ReLU networks
Optimal approximation of continuous functions by very deep ReLU networks
Dmitry Yarotsky
192
293
0
10 Feb 2018
Approximation beats concentration? An approximation view on inference
  with smooth radial kernels
Approximation beats concentration? An approximation view on inference with smooth radial kernels
M. Belkin
95
69
0
10 Jan 2018
Optimal approximation of piecewise smooth functions using deep ReLU
  neural networks
Optimal approximation of piecewise smooth functions using deep ReLU neural networks
P. Petersen
Felix Voigtländer
223
475
0
15 Sep 2017
Nearly-tight VC-dimension and pseudodimension bounds for piecewise
  linear neural networks
Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks
Peter L. Bartlett
Nick Harvey
Christopher Liaw
Abbas Mehrabian
208
432
0
08 Mar 2017
Error bounds for approximations with deep ReLU networks
Error bounds for approximations with deep ReLU networks
Dmitry Yarotsky
195
1,230
0
03 Oct 2016
L p -norm Sauer-Shelah Lemma for Margin Multi-category Classifiers
L p -norm Sauer-Shelah Lemma for Margin Multi-category Classifiers
Y. Guermeur
61
22
0
26 Sep 2016
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
367
609
0
14 Feb 2016
Covering Numbers for Convex Functions
Covering Numbers for Convex Functions
Adityanand Guntuboyina
B. Sen
89
77
0
31 Mar 2012
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