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Relating Regularization and Generalization through the Intrinsic Dimension of Activations

Relating Regularization and Generalization through the Intrinsic Dimension of Activations

Bradley Brown
Jordan Juravsky
Anthony L. Caterini
G. Loaiza-Ganem
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Papers citing "Relating Regularization and Generalization through the Intrinsic Dimension of Activations"

4 / 4 papers shown
Title
Why neural networks find simple solutions: the many regularizers of geometric complexity
Why neural networks find simple solutions: the many regularizers of geometric complexity
Benoit Dherin
Michael Munn
M. Rosca
David Barrett
53
30
0
27 Sep 2022
Tangent Space and Dimension Estimation with the Wasserstein Distance
Tangent Space and Dimension Estimation with the Wasserstein Distance
Uzu Lim
Harald Oberhauser
Vidit Nanda
37
8
0
12 Oct 2021
The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions
The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions
Vanessa D’Amario
S. Srivastava
Tomotake Sasaki
Xavier Boix
AAML
14
2
0
13 Jul 2021
The Intrinsic Dimension of Images and Its Impact on Learning
The Intrinsic Dimension of Images and Its Impact on Learning
Phillip E. Pope
Chen Zhu
Ahmed Abdelkader
Micah Goldblum
Tom Goldstein
189
259
0
18 Apr 2021