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Understanding the Generalization Benefit of Normalization Layers:
  Sharpness Reduction

Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction

14 June 2022
Kaifeng Lyu
Zhiyuan Li
Sanjeev Arora
    FAtt
ArXivPDFHTML

Papers citing "Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction"

14 / 14 papers shown
Title
Novel Concept-Oriented Synthetic Data approach for Training Generative AI-Driven Crystal Grain Analysis Using Diffusion Model
Novel Concept-Oriented Synthetic Data approach for Training Generative AI-Driven Crystal Grain Analysis Using Diffusion Model
Ahmed Sobhi Saleh
Kristof Croes
Hajdin Ceric
Ingrid De Wolf
Houman Zahedmanesh
DiffM
24
0
0
21 Apr 2025
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
20
0
0
05 Apr 2025
Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late in Training
Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late in Training
Zhanpeng Zhou
Mingze Wang
Yuchen Mao
Bingrui Li
Junchi Yan
AAML
57
0
0
14 Oct 2024
Does SGD really happen in tiny subspaces?
Does SGD really happen in tiny subspaces?
Minhak Song
Kwangjun Ahn
Chulhee Yun
56
4
1
25 May 2024
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To
  Achieve Better Generalization
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization
Kaiyue Wen
Zhiyuan Li
Tengyu Ma
FAtt
22
26
0
20 Jul 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
23
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
24
16
0
19 May 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
Agustinus Kristiadi
Felix Dangel
Philipp Hennig
17
10
0
14 Feb 2023
Understanding Incremental Learning of Gradient Descent: A Fine-grained
  Analysis of Matrix Sensing
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing
Jikai Jin
Zhiyuan Li
Kaifeng Lyu
S. Du
Jason D. Lee
MLT
31
34
0
27 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
31
36
0
14 Dec 2022
How Does Sharpness-Aware Minimization Minimize Sharpness?
How Does Sharpness-Aware Minimization Minimize Sharpness?
Kaiyue Wen
Tengyu Ma
Zhiyuan Li
AAML
21
47
0
10 Nov 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
64
35
0
07 Oct 2022
On the Implicit Bias in Deep-Learning Algorithms
On the Implicit Bias in Deep-Learning Algorithms
Gal Vardi
FedML
AI4CE
25
72
0
26 Aug 2022
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge
  of Stability
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability
Z. Li
Zixuan Wang
Jian Li
11
42
0
26 Jul 2022
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