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Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD
  Training

Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training

28 May 2024
Anchit Jain
Rozhin Nobahari
A. Baratin
Stefano Sarao Mannelli
ArXivPDFHTML

Papers citing "Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training"

15 / 15 papers shown
Title
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory
Francesco Mori
Stefano Sarao Mannelli
Francesca Mignacco
146
3
0
26 Sep 2024
Initial Guessing Bias: How Untrained Networks Favor Some Classes
Initial Guessing Bias: How Untrained Networks Favor Some Classes
Emanuele Francazi
Aurelien Lucchi
Marco Baity-Jesi
AI4CE
48
4
0
01 Jun 2023
High-dimensional limit theorems for SGD: Effective dynamics and critical
  scaling
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Gerard Ben Arous
Reza Gheissari
Aukosh Jagannath
96
58
0
08 Jun 2022
Just Train Twice: Improving Group Robustness without Training Group
  Information
Just Train Twice: Improving Group Robustness without Training Group Information
Emmy Liu
Behzad Haghgoo
Annie S. Chen
Aditi Raghunathan
Pang Wei Koh
Shiori Sagawa
Percy Liang
Chelsea Finn
OOD
88
561
0
19 Jul 2021
Understanding the Failure Modes of Out-of-Distribution Generalization
Understanding the Failure Modes of Out-of-Distribution Generalization
Vaishnavh Nagarajan
Anders Andreassen
Behnam Neyshabur
OOD
OODD
56
177
0
29 Oct 2020
The Pitfalls of Simplicity Bias in Neural Networks
The Pitfalls of Simplicity Bias in Neural Networks
Harshay Shah
Kaustav Tamuly
Aditi Raghunathan
Prateek Jain
Praneeth Netrapalli
AAML
67
359
0
13 Jun 2020
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
188
379
0
09 May 2020
Shortcut Learning in Deep Neural Networks
Shortcut Learning in Deep Neural Networks
Robert Geirhos
J. Jacobsen
Claudio Michaelis
R. Zemel
Wieland Brendel
Matthias Bethge
Felix Wichmann
201
2,048
0
16 Apr 2020
Distributionally Robust Neural Networks for Group Shifts: On the
  Importance of Regularization for Worst-Case Generalization
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa
Pang Wei Koh
Tatsunori B. Hashimoto
Percy Liang
OOD
97
1,241
0
20 Nov 2019
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting
Marc Lelarge
Léo Miolane
47
28
0
08 Jul 2019
On the Spectral Bias of Neural Networks
On the Spectral Bias of Neural Networks
Nasim Rahaman
A. Baratin
Devansh Arpit
Felix Dräxler
Min Lin
Fred Hamprecht
Yoshua Bengio
Aaron Courville
141
1,438
0
22 Jun 2018
Implicit Bias of Gradient Descent on Linear Convolutional Networks
Implicit Bias of Gradient Descent on Linear Convolutional Networks
Suriya Gunasekar
Jason D. Lee
Daniel Soudry
Nathan Srebro
MDE
124
411
0
01 Jun 2018
A Closer Look at Memorization in Deep Networks
A Closer Look at Memorization in Deep Networks
Devansh Arpit
Stanislaw Jastrzebski
Nicolas Ballas
David M. Krueger
Emmanuel Bengio
...
Tegan Maharaj
Asja Fischer
Aaron Courville
Yoshua Bengio
Simon Lacoste-Julien
TDI
122
1,816
0
16 Jun 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art
Fairness in Criminal Justice Risk Assessments: The State of the Art
R. Berk
Hoda Heidari
S. Jabbari
Michael Kearns
Aaron Roth
49
994
0
27 Mar 2017
In Search of the Real Inductive Bias: On the Role of Implicit
  Regularization in Deep Learning
In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning
Behnam Neyshabur
Ryota Tomioka
Nathan Srebro
AI4CE
90
657
0
20 Dec 2014
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