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DAC-MR: Data Augmentation Consistency Based Meta-Regularization for
  Meta-Learning

DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning

13 May 2023
Jun Shu
Xiang Yuan
Deyu Meng
Zongben Xu
ArXivPDFHTML

Papers citing "DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning"

40 / 140 papers shown
Title
Generalized Cross Entropy Loss for Training Deep Neural Networks with
  Noisy Labels
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels
Zhilu Zhang
M. Sabuncu
NoLa
60
2,580
0
20 May 2018
Task-Agnostic Meta-Learning for Few-shot Learning
Task-Agnostic Meta-Learning for Few-shot Learning
Muhammad Abdullah Jamal
Guo-Jun Qi
M. Shah
74
461
0
20 May 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely
  Noisy Labels
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Bo Han
Quanming Yao
Xingrui Yu
Gang Niu
Miao Xu
Weihua Hu
Ivor Tsang
Masashi Sugiyama
NoLa
82
2,051
0
18 Apr 2018
Meta-Learning Update Rules for Unsupervised Representation Learning
Meta-Learning Update Rules for Unsupervised Representation Learning
Luke Metz
Niru Maheswaranathan
Brian Cheung
Jascha Narain Sohl-Dickstein
SSL
OOD
51
122
0
31 Mar 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
125
1,419
0
24 Mar 2018
Meta-Learning for Semi-Supervised Few-Shot Classification
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren
Eleni Triantafillou
S. S. Ravi
Jake C. Snell
Kevin Swersky
J. Tenenbaum
Hugo Larochelle
R. Zemel
SSL
59
1,278
0
02 Mar 2018
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe
  Noise
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise
Dan Hendrycks
Mantas Mazeika
Duncan Wilson
Kevin Gimpel
NoLa
122
553
0
14 Feb 2018
Evolved Policy Gradients
Evolved Policy Gradients
Rein Houthooft
Richard Y. Chen
Phillip Isola
Bradly C. Stadie
Filip Wolski
Jonathan Ho
Pieter Abbeel
76
226
0
13 Feb 2018
Explicit Inductive Bias for Transfer Learning with Convolutional
  Networks
Explicit Inductive Bias for Transfer Learning with Convolutional Networks
Xuhong Li
Yves Grandvalet
Franck Davoine
SSL
65
349
0
05 Feb 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks
  on Corrupted Labels
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels
Lu Jiang
Zhengyuan Zhou
Thomas Leung
Li Li
Li Fei-Fei
NoLa
88
1,448
0
14 Dec 2017
Learning to Compare: Relation Network for Few-Shot Learning
Learning to Compare: Relation Network for Few-Shot Learning
Flood Sung
Yongxin Yang
Li Zhang
Tao Xiang
Philip Torr
Timothy M. Hospedales
203
4,035
0
16 Nov 2017
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
238
9,687
0
25 Oct 2017
VisDA: The Visual Domain Adaptation Challenge
VisDA: The Visual Domain Adaptation Challenge
Xingchao Peng
Ben Usman
Neela Kaushik
Judy Hoffman
Dequan Wang
Kate Saenko
OOD
66
795
0
18 Oct 2017
Learning to Generalize: Meta-Learning for Domain Generalization
Learning to Generalize: Meta-Learning for Domain Generalization
Da Li
Yongxin Yang
Yi-Zhe Song
Timothy M. Hospedales
OOD
82
1,404
0
10 Oct 2017
Neural Optimizer Search with Reinforcement Learning
Neural Optimizer Search with Reinforcement Learning
Irwan Bello
Barret Zoph
Vijay Vasudevan
Quoc V. Le
ODL
45
385
0
21 Sep 2017
Multi-task Self-Supervised Visual Learning
Multi-task Self-Supervised Visual Learning
Carl Doersch
Andrew Zisserman
SSL
56
631
0
25 Aug 2017
WebVision Database: Visual Learning and Understanding from Web Data
WebVision Database: Visual Learning and Understanding from Web Data
Wen Li
Limin Wang
Wei Li
E. Agustsson
Luc Van Gool
VLM
70
435
0
09 Aug 2017
Gradient Episodic Memory for Continual Learning
Gradient Episodic Memory for Continual Learning
David Lopez-Paz
MarcÁurelio Ranzato
VLM
CLL
72
2,684
0
26 Jun 2017
Deep Hashing Network for Unsupervised Domain Adaptation
Deep Hashing Network for Unsupervised Domain Adaptation
Hemanth Venkateswara
José Eusébio
Shayok Chakraborty
S. Panchanathan
OOD
102
2,030
0
22 Jun 2017
Virtual Adversarial Training: A Regularization Method for Supervised and
  Semi-Supervised Learning
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato
S. Maeda
Masanori Koyama
S. Ishii
GAN
118
2,728
0
13 Apr 2017
Prototypical Networks for Few-shot Learning
Prototypical Networks for Few-shot Learning
Jake C. Snell
Kevin Swersky
R. Zemel
213
8,072
0
15 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
759
11,793
0
09 Mar 2017
iCaRL: Incremental Classifier and Representation Learning
iCaRL: Incremental Classifier and Representation Learning
Sylvestre-Alvise Rebuffi
Alexander Kolesnikov
G. Sperl
Christoph H. Lampert
CLL
OOD
91
3,713
0
23 Nov 2016
Learning to reinforcement learn
Learning to reinforcement learn
Jane X. Wang
Z. Kurth-Nelson
Dhruva Tirumala
Hubert Soyer
Joel Z Leibo
Rémi Munos
Charles Blundell
D. Kumaran
M. Botvinick
OffRL
70
974
0
17 Nov 2016
Reinforcement Learning with Unsupervised Auxiliary Tasks
Reinforcement Learning with Unsupervised Auxiliary Tasks
Max Jaderberg
Volodymyr Mnih
Wojciech M. Czarnecki
Tom Schaul
Joel Z Leibo
David Silver
Koray Kavukcuoglu
SSL
43
1,225
0
16 Nov 2016
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
RL2^22: Fast Reinforcement Learning via Slow Reinforcement Learning
Yan Duan
John Schulman
Xi Chen
Peter L. Bartlett
Ilya Sutskever
Pieter Abbeel
OffRL
67
1,011
0
09 Nov 2016
Temporal Ensembling for Semi-Supervised Learning
Temporal Ensembling for Semi-Supervised Learning
S. Laine
Timo Aila
UQCV
162
2,543
0
07 Oct 2016
Making Deep Neural Networks Robust to Label Noise: a Loss Correction
  Approach
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
Giorgio Patrini
A. Rozza
A. Menon
Richard Nock
Zhuang Li
NoLa
83
1,447
0
13 Sep 2016
Learning to learn by gradient descent by gradient descent
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz
Misha Denil
Sergio Gomez Colmenarejo
Matthew W. Hoffman
David Pfau
Tom Schaul
Brendan Shillingford
Nando de Freitas
82
2,000
0
14 Jun 2016
Matching Networks for One Shot Learning
Matching Networks for One Shot Learning
Oriol Vinyals
Charles Blundell
Timothy Lillicrap
Koray Kavukcuoglu
Daan Wierstra
VLM
290
7,299
0
13 Jun 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.4K
192,638
0
10 Dec 2015
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
478
27,231
0
02 Dec 2015
Return of Frustratingly Easy Domain Adaptation
Return of Frustratingly Easy Domain Adaptation
Baochen Sun
Jiashi Feng
Kate Saenko
OOD
60
1,831
0
17 Nov 2015
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
343
9,418
0
28 May 2015
The Benefit of Multitask Representation Learning
The Benefit of Multitask Representation Learning
Andreas Maurer
Massimiliano Pontil
Bernardino Romera-Paredes
SSL
74
375
0
23 May 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
300
43,154
0
11 Feb 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
163
18,922
0
20 Dec 2014
How transferable are features in deep neural networks?
How transferable are features in deep neural networks?
J. Yosinski
Jeff Clune
Yoshua Bengio
Hod Lipson
OOD
145
8,309
0
06 Nov 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
1.1K
39,383
0
01 Sep 2014
Fine-Grained Visual Classification of Aircraft
Fine-Grained Visual Classification of Aircraft
Subhransu Maji
Esa Rahtu
Arno Solin
Matthew Blaschko
Andrea Vedaldi
86
2,227
0
21 Jun 2013
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