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Critical Influence of Overparameterization on Sharpness-aware Minimization

Critical Influence of Overparameterization on Sharpness-aware Minimization

29 November 2023
Sungbin Shin
Dongyeop Lee
Maksym Andriushchenko
Namhoon Lee
    AAML
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Papers citing "Critical Influence of Overparameterization on Sharpness-aware Minimization"

10 / 10 papers shown
Title
SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
Dahun Shin
Dongyeop Lee
Jinseok Chung
Namhoon Lee
ODL
AAML
84
0
0
25 Feb 2025
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
301
11,730
0
04 Mar 2022
Anticorrelated Noise Injection for Improved Generalization
Anticorrelated Noise Injection for Improved Generalization
Antonio Orvieto
Hans Kersting
F. Proske
Francis R. Bach
Aurélien Lucchi
42
44
0
06 Feb 2022
Sharpness-Aware Minimization Improves Language Model Generalization
Sharpness-Aware Minimization Improves Language Model Generalization
Dara Bahri
H. Mobahi
Yi Tay
108
82
0
16 Oct 2021
Differentially Private Fine-tuning of Language Models
Differentially Private Fine-tuning of Language Models
Da Yu
Saurabh Naik
A. Backurs
Sivakanth Gopi
Huseyin A. Inan
...
Y. Lee
Andre Manoel
Lukas Wutschitz
Sergey Yekhanin
Huishuai Zhang
128
258
0
13 Oct 2021
Efficient Sharpness-aware Minimization for Improved Training of Neural
  Networks
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
Jiawei Du
Hanshu Yan
Jiashi Feng
Joey Tianyi Zhou
Liangli Zhen
Rick Siow Mong Goh
Vincent Y. F. Tan
AAML
99
108
0
07 Oct 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler
Dan Alistarh
Tal Ben-Nun
Nikoli Dryden
Alexandra Peste
MQ
128
679
0
31 Jan 2021
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
220
3,054
0
23 Jan 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
273
2,696
0
15 Sep 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the
  Polyak-Łojasiewicz Condition
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Hamed Karimi
J. Nutini
Mark W. Schmidt
114
1,190
0
16 Aug 2016
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