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Reweighting Augmented Samples by Minimizing the Maximal Expected Loss

Reweighting Augmented Samples by Minimizing the Maximal Expected Loss

16 March 2021
Mingyang Yi
Lu Hou
Lifeng Shang
Xin Jiang
Qun Liu
Zhi-Ming Ma
ArXivPDFHTML

Papers citing "Reweighting Augmented Samples by Minimizing the Maximal Expected Loss"

13 / 13 papers shown
Title
AdvAug: Robust Adversarial Augmentation for Neural Machine Translation
AdvAug: Robust Adversarial Augmentation for Neural Machine Translation
Yong Cheng
Lu Jiang
Wolfgang Macherey
Jacob Eisenstein
63
117
0
21 Jun 2020
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language
  Models through Principled Regularized Optimization
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
Haoming Jiang
Pengcheng He
Weizhu Chen
Xiaodong Liu
Jianfeng Gao
T. Zhao
73
561
0
08 Nov 2019
FreeLB: Enhanced Adversarial Training for Natural Language Understanding
FreeLB: Enhanced Adversarial Training for Natural Language Understanding
Chen Zhu
Yu Cheng
Zhe Gan
S. Sun
Tom Goldstein
Jingjing Liu
AAML
255
441
0
25 Sep 2019
TinyBERT: Distilling BERT for Natural Language Understanding
TinyBERT: Distilling BERT for Natural Language Understanding
Xiaoqi Jiao
Yichun Yin
Lifeng Shang
Xin Jiang
Xiao Chen
Linlin Li
F. Wang
Qun Liu
VLM
87
1,855
0
23 Sep 2019
Adversarial Training Can Hurt Generalization
Adversarial Training Can Hurt Generalization
Aditi Raghunathan
Sang Michael Xie
Fanny Yang
John C. Duchi
Percy Liang
79
242
0
14 Jun 2019
Robust Neural Machine Translation with Doubly Adversarial Inputs
Robust Neural Machine Translation with Doubly Adversarial Inputs
Yong Cheng
Lu Jiang
Wolfgang Macherey
AAML
59
255
0
06 Jun 2019
Unsupervised Data Augmentation for Consistency Training
Unsupervised Data Augmentation for Consistency Training
Qizhe Xie
Zihang Dai
Eduard H. Hovy
Minh-Thang Luong
Quoc V. Le
124
2,314
0
29 Apr 2019
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text
  Classification Tasks
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
Jason W. Wei
Kai Zou
99
1,949
0
31 Jan 2019
Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and
  Stopping Criteria for Neural Machine Translation
Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and Stopping Criteria for Neural Machine Translation
Yilin Yang
Liang Huang
Mingbo Ma
52
92
0
28 Aug 2018
AutoAugment: Learning Augmentation Policies from Data
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
118
1,771
0
24 May 2018
Learning to Reweight Examples for Robust Deep Learning
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren
Wenyuan Zeng
Binh Yang
R. Urtasun
OOD
NoLa
139
1,424
0
24 Mar 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
261
12,029
0
19 Jun 2017
Accelerating Minibatch Stochastic Gradient Descent using Stratified
  Sampling
Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling
P. Zhao
Tong Zhang
66
90
0
13 May 2014
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