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2006.07965
Cited By
Meta Approach to Data Augmentation Optimization
14 June 2020
Ryuichiro Hataya
Jan Zdenek
Kazuki Yoshizoe
Hideki Nakayama
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Papers citing
"Meta Approach to Data Augmentation Optimization"
42 / 42 papers shown
Title
Learning Data Augmentation with Online Bilevel Optimization for Image Classification
Saypraseuth Mounsaveng
I. Laradji
Ismail Ben Ayed
David Vazquez
M. Pedersoli
33
36
0
25 Jun 2020
DADA: Differentiable Automatic Data Augmentation
Yonggang Li
Guosheng Hu
Yongtao Wang
Timothy M. Hospedales
N. Robertson
Yongxin Yang
49
109
0
08 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
194
18,523
0
13 Feb 2020
Adversarial AutoAugment
Xinyu Zhang
Qiang-qiang Wang
Jian Zhang
Zhaobai Zhong
AAML
57
197
0
24 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
237
42,038
0
03 Dec 2019
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
David Berthelot
Nicholas Carlini
E. D. Cubuk
Alexey Kurakin
Kihyuk Sohn
Han Zhang
Colin Raffel
78
676
0
21 Nov 2019
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation
Ryuichiro Hataya
Jan Zdenek
Kazuki Yoshizoe
Hideki Nakayama
47
204
0
16 Nov 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
107
11,959
0
13 Nov 2019
Adversarial Transformations for Semi-Supervised Learning
Teppei Suzuki
Ikuro Sato
24
13
0
13 Nov 2019
Optimizing Millions of Hyperparameters by Implicit Differentiation
Jonathan Lorraine
Paul Vicol
David Duvenaud
DD
101
409
0
06 Nov 2019
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
F. Mokhayeri
Dmytro Mishkin
Daniel Ponsa
Ethan Rublee
Gary R. Bradski
VLM
AI4TS
104
353
0
05 Oct 2019
RandAugment: Practical automated data augmentation with a reduced search space
E. D. Cubuk
Barret Zoph
Jonathon Shlens
Quoc V. Le
MQ
183
3,458
0
30 Sep 2019
Meta-Learning with Implicit Gradients
Aravind Rajeswaran
Chelsea Finn
Sham Kakade
Sergey Levine
84
848
0
10 Sep 2019
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation
Raphael Gontijo-Lopes
Dong Yin
Ben Poole
Justin Gilmer
E. D. Cubuk
AAML
110
205
0
06 Jun 2019
Online Hyper-parameter Learning for Auto-Augmentation Strategy
Chen Lin
Minghao Guo
Chuming Li
Yuan Xin
Wei Wu
Dahua Lin
Wanli Ouyang
Junjie Yan
ODL
35
84
0
17 May 2019
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
Daniel Ho
Eric Liang
Ion Stoica
Pieter Abbeel
Xi Chen
51
402
0
14 May 2019
Fast AutoAugment
Sungbin Lim
Ildoo Kim
Taesup Kim
Chiheon Kim
Sungwoong Kim
65
593
0
01 May 2019
Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets
Riccardo Volpi
Vittorio Murino
52
29
0
28 Mar 2019
Truncated Back-propagation for Bilevel Optimization
Amirreza Shaban
Ching-An Cheng
Nathan Hatch
Byron Boots
77
265
0
25 Oct 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi
P. Frasconi
Saverio Salzo
Riccardo Grazzi
Massimiliano Pontil
171
722
0
13 Jun 2018
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
93
1,764
0
24 May 2018
Reviving and Improving Recurrent Back-Propagation
Renjie Liao
Yuwen Xiong
Ethan Fetaya
Lisa Zhang
Kijung Yoon
Xaq Pitkow
R. Urtasun
R. Zemel
BDL
59
118
0
16 Mar 2018
On First-Order Meta-Learning Algorithms
Alex Nichol
Joshua Achiam
John Schulman
199
2,226
0
08 Mar 2018
Data Augmentation Generative Adversarial Networks
Antreas Antoniou
Amos Storkey
Harrison Edwards
MedIm
GAN
110
1,069
0
12 Nov 2017
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
236
9,687
0
25 Oct 2017
Learning to Compose Domain-Specific Transformations for Data Augmentation
Alexander J. Ratner
Henry R. Ehrenberg
Zeshan Hussain
Jared A. Dunnmon
Christopher Ré
61
349
0
06 Sep 2017
Improved Regularization of Convolutional Neural Networks with Cutout
Terrance Devries
Graham W. Taylor
81
3,739
0
15 Aug 2017
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
134
2,854
0
14 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
754
11,793
0
09 Mar 2017
Dataset Augmentation in Feature Space
Terrance Devries
Graham W. Taylor
47
425
0
17 Feb 2017
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
214
5,323
0
03 Nov 2016
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
622
36,599
0
25 Aug 2016
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
222
8,030
0
13 Aug 2016
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
254
7,951
0
23 May 2016
Hyperparameter optimization with approximate gradient
Fabian Pedregosa
85
449
0
07 Feb 2016
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.3K
192,638
0
10 Dec 2015
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation
Søren Hauberg
Oren Freifeld
Anders Boesen Lindbo Larsen
John W. Fisher III
Lars Kai Hansen
31
154
0
09 Oct 2015
Gradient-based Hyperparameter Optimization through Reversible Learning
D. Maclaurin
David Duvenaud
Ryan P. Adams
DD
165
941
0
11 Feb 2015
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
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Yoshua Bengio
Nicholas Léonard
Aaron Courville
303
3,099
0
15 Aug 2013
Fine-Grained Visual Classification of Aircraft
Subhransu Maji
Esa Rahtu
Arno Solin
Matthew Blaschko
Andrea Vedaldi
80
2,227
0
21 Jun 2013
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek
Hugo Larochelle
Ryan P. Adams
275
7,883
0
13 Jun 2012
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