ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2209.15594
  4. Cited By
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of
  Stability

Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability

30 September 2022
Alexandru Damian
Eshaan Nichani
Jason D. Lee
ArXivPDFHTML

Papers citing "Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability"

29 / 29 papers shown
Title
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes
Ruiqi Zhang
Jingfeng Wu
Licong Lin
Peter L. Bartlett
30
0
0
05 Apr 2025
Feature Learning Beyond the Edge of Stability
Feature Learning Beyond the Edge of Stability
Dávid Terjék
MLT
46
0
0
18 Feb 2025
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos
Dayal Singh Kalra
Tianyu He
M. Barkeshli
52
4
0
17 Feb 2025
The Optimization Landscape of SGD Across the Feature Learning Strength
The Optimization Landscape of SGD Across the Feature Learning Strength
Alexander B. Atanasov
Alexandru Meterez
James B. Simon
Cengiz Pehlevan
43
2
0
06 Oct 2024
How Neural Networks Learn the Support is an Implicit Regularization
  Effect of SGD
How Neural Networks Learn the Support is an Implicit Regularization Effect of SGD
Pierfrancesco Beneventano
Andrea Pinto
Tomaso A. Poggio
MLT
32
1
0
17 Jun 2024
Does SGD really happen in tiny subspaces?
Does SGD really happen in tiny subspaces?
Minhak Song
Kwangjun Ahn
Chulhee Yun
71
5
1
25 May 2024
Why is SAM Robust to Label Noise?
Why is SAM Robust to Label Noise?
Christina Baek
Zico Kolter
Aditi Raghunathan
NoLa
AAML
43
9
0
06 May 2024
High dimensional analysis reveals conservative sharpening and a stochastic edge of stability
High dimensional analysis reveals conservative sharpening and a stochastic edge of stability
Atish Agarwala
Jeffrey Pennington
41
3
0
30 Apr 2024
Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization
Implicit Bias of AdamW: ℓ∞\ell_\inftyℓ∞​ Norm Constrained Optimization
Shuo Xie
Zhiyuan Li
OffRL
47
13
0
05 Apr 2024
From Stability to Chaos: Analyzing Gradient Descent Dynamics in
  Quadratic Regression
From Stability to Chaos: Analyzing Gradient Descent Dynamics in Quadratic Regression
Xuxing Chen
Krishnakumar Balasubramanian
Promit Ghosal
Bhavya Agrawalla
33
7
0
02 Oct 2023
Small-scale proxies for large-scale Transformer training instabilities
Small-scale proxies for large-scale Transformer training instabilities
Mitchell Wortsman
Peter J. Liu
Lechao Xiao
Katie Everett
A. Alemi
...
Jascha Narain Sohl-Dickstein
Kelvin Xu
Jaehoon Lee
Justin Gilmer
Simon Kornblith
37
81
0
25 Sep 2023
Sharpness-Aware Minimization and the Edge of Stability
Sharpness-Aware Minimization and the Edge of Stability
Philip M. Long
Peter L. Bartlett
AAML
27
9
0
21 Sep 2023
How to escape sharp minima with random perturbations
How to escape sharp minima with random perturbations
Kwangjun Ahn
Ali Jadbabaie
S. Sra
ODL
32
6
0
25 May 2023
Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow
  Solutions in Scalar Networks and Beyond
Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond
Itai Kreisler
Mor Shpigel Nacson
Daniel Soudry
Y. Carmon
30
13
0
22 May 2023
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of
  Stability
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability
Jingfeng Wu
Vladimir Braverman
Jason D. Lee
32
17
0
19 May 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean
  Field Neural Networks
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
Blake Bordelon
Cengiz Pehlevan
MLT
38
29
0
06 Apr 2023
SAM operates far from home: eigenvalue regularization as a dynamical
  phenomenon
SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
Atish Agarwala
Yann N. Dauphin
21
20
0
17 Feb 2023
On a continuous time model of gradient descent dynamics and instability
  in deep learning
On a continuous time model of gradient descent dynamics and instability in deep learning
Mihaela Rosca
Yan Wu
Chongli Qin
Benoit Dherin
18
6
0
03 Feb 2023
Training trajectories, mini-batch losses and the curious role of the
  learning rate
Training trajectories, mini-batch losses and the curious role of the learning rate
Mark Sandler
A. Zhmoginov
Max Vladymyrov
Nolan Miller
ODL
28
10
0
05 Jan 2023
Learning threshold neurons via the "edge of stability"
Learning threshold neurons via the "edge of stability"
Kwangjun Ahn
Sébastien Bubeck
Sinho Chewi
Y. Lee
Felipe Suarez
Yi Zhang
MLT
38
36
0
14 Dec 2022
Second-order regression models exhibit progressive sharpening to the
  edge of stability
Second-order regression models exhibit progressive sharpening to the edge of stability
Atish Agarwala
Fabian Pedregosa
Jeffrey Pennington
35
26
0
10 Oct 2022
On skip connections and normalisation layers in deep optimisation
On skip connections and normalisation layers in deep optimisation
L. MacDonald
Jack Valmadre
Hemanth Saratchandran
Simon Lucey
ODL
19
1
0
10 Oct 2022
Understanding Edge-of-Stability Training Dynamics with a Minimalist
  Example
Understanding Edge-of-Stability Training Dynamics with a Minimalist Example
Xingyu Zhu
Zixuan Wang
Xiang Wang
Mo Zhou
Rong Ge
66
35
0
07 Oct 2022
The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines
  and Drifting Towards Wide Minima
The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima
Peter L. Bartlett
Philip M. Long
Olivier Bousquet
76
34
0
04 Oct 2022
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
62
58
0
08 Jun 2022
Understanding Gradient Descent on Edge of Stability in Deep Learning
Understanding Gradient Descent on Edge of Stability in Deep Learning
Sanjeev Arora
Zhiyuan Li
A. Panigrahi
MLT
83
89
0
19 May 2022
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework
Zhiyuan Li
Tianhao Wang
Sanjeev Arora
MLT
90
98
0
13 Oct 2021
The large learning rate phase of deep learning: the catapult mechanism
The large learning rate phase of deep learning: the catapult mechanism
Aitor Lewkowycz
Yasaman Bahri
Ethan Dyer
Jascha Narain Sohl-Dickstein
Guy Gur-Ari
ODL
159
234
0
04 Mar 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
308
2,890
0
15 Sep 2016
1