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A Lipschitz spaces view of infinitely wide shallow neural networks

A Lipschitz spaces view of infinitely wide shallow neural networks

18 October 2024
Francesca Bartolucci
Marcello Carioni
José A. Iglesias
Yury Korolev
Emanuele Naldi
Stefano Vigogna
ArXivPDFHTML

Papers citing "A Lipschitz spaces view of infinitely wide shallow neural networks"

13 / 13 papers shown
Title
Embeddings between Barron spaces with higher order activation functions
Embeddings between Barron spaces with higher order activation functions
T. J. Heeringa
L. Spek
Felix L. Schwenninger
C. Brune
75
3
0
25 May 2023
Duality for Neural Networks through Reproducing Kernel Banach Spaces
Duality for Neural Networks through Reproducing Kernel Banach Spaces
L. Spek
T. J. Heeringa
Felix L. Schwenninger
C. Brune
76
13
0
09 Nov 2022
What Kinds of Functions do Deep Neural Networks Learn? Insights from
  Variational Spline Theory
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory
Rahul Parhi
Robert D. Nowak
MLT
62
71
0
07 May 2021
Two-layer neural networks with values in a Banach space
Two-layer neural networks with values in a Banach space
Yury Korolev
58
24
0
05 May 2021
Convex regularization in statistical inverse learning problems
Convex regularization in statistical inverse learning problems
T. Bubba
Martin Burger
T. Helin
Luca Ratti
32
9
0
18 Feb 2021
Deep Equals Shallow for ReLU Networks in Kernel Regimes
Deep Equals Shallow for ReLU Networks in Kernel Regimes
A. Bietti
Francis R. Bach
63
90
0
30 Sep 2020
Representation Transfer by Optimal Transport
Representation Transfer by Optimal Transport
Xuhong Li
Yves Grandvalet
Rémi Flamary
Nicolas Courty
Dejing Dou
OT
54
8
0
13 Jul 2020
When Do Neural Networks Outperform Kernel Methods?
When Do Neural Networks Outperform Kernel Methods?
Behrooz Ghorbani
Song Mei
Theodor Misiakiewicz
Andrea Montanari
86
188
0
24 Jun 2020
Fantastic Generalization Measures and Where to Find Them
Fantastic Generalization Measures and Where to Find Them
Yiding Jiang
Behnam Neyshabur
H. Mobahi
Dilip Krishnan
Samy Bengio
AI4CE
129
606
0
04 Dec 2019
Model Fusion via Optimal Transport
Model Fusion via Optimal Transport
Sidak Pal Singh
Martin Jaggi
MoMe
FedML
101
234
0
12 Oct 2019
Reconciling modern machine learning practice and the bias-variance
  trade-off
Reconciling modern machine learning practice and the bias-variance trade-off
M. Belkin
Daniel J. Hsu
Siyuan Ma
Soumik Mandal
227
1,647
0
28 Dec 2018
Deep Neural Networks as Gaussian Processes
Deep Neural Networks as Gaussian Processes
Jaehoon Lee
Yasaman Bahri
Roman Novak
S. Schoenholz
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCV
BDL
118
1,093
0
01 Nov 2017
Optimal Rates For Regularization Of Statistical Inverse Learning
  Problems
Optimal Rates For Regularization Of Statistical Inverse Learning Problems
Gilles Blanchard
Nicole Mücke
449
143
0
14 Apr 2016
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