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ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
International Conference on Machine Learning (ICML), 2021
23 February 2021
Jungmin Kwon
Jeongseop Kim
Hyunseong Park
I. Choi
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Papers citing
"ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks"
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Tackling covariate shift with node-based Bayesian neural networks
International Conference on Machine Learning (ICML), 2022
Trung Trinh
Markus Heinonen
Luigi Acerbi
Samuel Kaski
BDL
UQCV
221
7
0
06 Jun 2022
Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Clara Na
Sanket Vaibhav Mehta
Emma Strubell
276
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25 May 2022
Vision Transformers in 2022: An Update on Tiny ImageNet
Ethan Huynh
ViT
160
16
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21 May 2022
EXACT: How to Train Your Accuracy
Pattern Recognition Letters (PR), 2022
I. Karpukhin
Stanislav Dereka
Sergey Kolesnikov
238
0
0
19 May 2022
Multimodal Transformer for Nursing Activity Recognition
Momal Ijaz
Renato Diaz
Chong Chen
ViT
188
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09 Apr 2022
TransGeo: Transformer Is All You Need for Cross-view Image Geo-localization
Computer Vision and Pattern Recognition (CVPR), 2022
Sijie Zhu
M. Shah
Chong Chen
ViT
271
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31 Mar 2022
Improving Generalization in Federated Learning by Seeking Flat Minima
European Conference on Computer Vision (ECCV), 2022
Debora Caldarola
Barbara Caputo
Marco Ciccone
FedML
377
138
0
22 Mar 2022
Randomized Sharpness-Aware Training for Boosting Computational Efficiency in Deep Learning
Yang Zhao
Hao Zhang
Xiuyuan Hu
160
13
0
18 Mar 2022
Surrogate Gap Minimization Improves Sharpness-Aware Training
International Conference on Learning Representations (ICLR), 2022
Juntang Zhuang
Boqing Gong
Liangzhe Yuan
Huayu Chen
Hartwig Adam
Nicha Dvornek
S. Tatikonda
James Duncan
Ting Liu
300
196
0
15 Mar 2022
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning
International Conference on Machine Learning (ICML), 2022
Yang Zhao
Hao Zhang
Xiuyuan Hu
506
153
0
08 Feb 2022
When Do Flat Minima Optimizers Work?
Neural Information Processing Systems (NeurIPS), 2022
Jean Kaddour
Linqing Liu
Ricardo M. A. Silva
Matt J. Kusner
ODL
526
86
0
01 Feb 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Devansh Bisla
Jing Wang
A. Choromańska
331
45
0
20 Jan 2022
Generalized Wasserstein Dice Loss, Test-time Augmentation, and Transformers for the BraTS 2021 challenge
Lucas Fidon
Antonio Terpin
Ivan Ezhov
Johannes C. Paetzold
Sébastien Ourselin
Tom Vercauteren
ViT
MedIm
148
10
0
24 Dec 2021
Unsupervised Dense Information Retrieval with Contrastive Learning
Gautier Izacard
Mathilde Caron
Lucas Hosseini
Sebastian Riedel
Piotr Bojanowski
Armand Joulin
Edouard Grave
RALM
765
1,245
0
16 Dec 2021
Sharpness-Aware Minimization with Dynamic Reweighting
Wenxuan Zhou
Fangyu Liu
Huan Zhang
Muhao Chen
AAML
327
8
0
16 Dec 2021
Sharpness-aware Quantization for Deep Neural Networks
Jing Liu
Jianfei Cai
Bohan Zhuang
MQ
480
27
0
24 Nov 2021
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion
Computer Vision and Pattern Recognition (CVPR), 2021
Arthur Douillard
Alexandre Ramé
Guillaume Couairon
Matthieu Cord
CLL
390
385
0
22 Nov 2021
Exponential escape efficiency of SGD from sharp minima in non-stationary regime
Hikaru Ibayashi
Masaaki Imaizumi
289
5
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07 Nov 2021
Sharpness-Aware Minimization Improves Language Model Generalization
Dara Bahri
H. Mobahi
Yi Tay
474
116
0
16 Oct 2021
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
Jiawei Du
Hanshu Yan
Jiashi Feng
Qiufeng Wang
Liangli Zhen
Rick Siow Mong Goh
Vincent Y. F. Tan
AAML
416
160
0
07 Oct 2021
Perturbated Gradients Updating within Unit Space for Deep Learning
Ching-Hsun Tseng
Liu Cheng
Shin-Jye Lee
Xiaojun Zeng
373
5
0
01 Oct 2021
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability
Roman Levin
Manli Shu
Eitan Borgnia
Furong Huang
Micah Goldblum
Tom Goldstein
FAtt
AAML
117
12
0
03 Aug 2021
A novel multi-scale loss function for classification problems in machine learning
Journal of Computational Physics (JCP), 2021
L. Berlyand
Robert Creese
P. Jabin
145
4
0
04 Jun 2021
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M. Schmidt
Frank Schneider
Philipp Hennig
ODL
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186
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03 Jul 2020
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