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WeMix: How to Better Utilize Data Augmentation

WeMix: How to Better Utilize Data Augmentation

3 October 2020
Yi Tian Xu
Asaf Noy
Ming Lin
Qi Qian
Hao Li
R. L. Jin
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Papers citing "WeMix: How to Better Utilize Data Augmentation"

6 / 6 papers shown
Title
Resilient Constrained Learning
Resilient Constrained Learning
Ignacio Hounie
Alejandro Ribeiro
Luiz F. O. Chamon
21
9
0
04 Jun 2023
Context Normalization Layer with Applications
Context Normalization Layer with Applications
Bilal Faye
M. Dilmi
Hanene Azzag
M. Lebbah
D. Bouchaffra
21
0
0
14 Mar 2023
Automatic Data Augmentation via Invariance-Constrained Learning
Automatic Data Augmentation via Invariance-Constrained Learning
Ignacio Hounie
Luiz F. O. Chamon
Alejandro Ribeiro
23
10
0
29 Sep 2022
The Effects of Regularization and Data Augmentation are Class Dependent
The Effects of Regularization and Data Augmentation are Class Dependent
Randall Balestriero
Léon Bottou
Yann LeCun
28
94
0
07 Apr 2022
Bag of Tricks for Image Classification with Convolutional Neural
  Networks
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He
Zhi-Li Zhang
Hang Zhang
Zhongyue Zhang
Junyuan Xie
Mu Li
221
1,399
0
04 Dec 2018
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
133
1,198
0
16 Aug 2016
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