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Relating Regularization and Generalization through the Intrinsic
  Dimension of Activations

Relating Regularization and Generalization through the Intrinsic Dimension of Activations

23 November 2022
Bradley Brown
Jordan Juravsky
Anthony L. Caterini
G. Loaiza-Ganem
ArXivPDFHTML

Papers citing "Relating Regularization and Generalization through the Intrinsic Dimension of Activations"

5 / 5 papers shown
Title
Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations
Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations
Lorenzo Basile
Santiago Acevedo
Luca Bortolussi
Fabio Anselmi
Alex Rodriguez
50
4
0
22 Jun 2024
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
57
31
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
44
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
26
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
197
262
0
18 Apr 2021
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