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Self-supervised debiasing using low rank regularization
v1v2 (latest)

Self-supervised debiasing using low rank regularization

11 October 2022
Geon Yeong Park
Chanyong Jung
Sangmin Lee
Jong Chul Ye
Sang Wan Lee
    CMLSSL
ArXiv (abs)PDFHTML

Papers citing "Self-supervised debiasing using low rank regularization"

50 / 59 papers shown
Title
Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of
  Biases-Specific Experts
Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of Biases-Specific Experts
Jiaxuan Li
D. Vo
Hideki Nakayama
65
3
0
19 Aug 2023
Training Debiased Subnetworks with Contrastive Weight Pruning
Training Debiased Subnetworks with Contrastive Weight Pruning
Geon Yeong Park
Sangmin Lee
Sang Wan Lee
Jong Chul Ye
CML
100
13
0
11 Oct 2022
Discover and Mitigate Unknown Biases with Debiasing Alternate Networks
Discover and Mitigate Unknown Biases with Debiasing Alternate Networks
Zhiheng Li
A. Hoogs
Chenliang Xu
83
55
0
20 Jul 2022
Hard Negative Sampling Strategies for Contrastive Representation
  Learning
Hard Negative Sampling Strategies for Contrastive Representation Learning
Afrina Tabassum
Muntasir Wahed
Hoda Eldardiry
Ismini Lourentzou
SSL
98
25
0
02 Jun 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious
  Correlations
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
Polina Kirichenko
Pavel Izmailov
A. Wilson
OOD
91
339
0
06 Apr 2022
Investigating Why Contrastive Learning Benefits Robustness Against Label
  Noise
Investigating Why Contrastive Learning Benefits Robustness Against Label Noise
Yihao Xue
Kyle Whitecross
Baharan Mirzasoleiman
SSLNoLa
94
54
0
29 Jan 2022
Simple data balancing achieves competitive worst-group-accuracy
Simple data balancing achieves competitive worst-group-accuracy
Badr Youbi Idrissi
Martín Arjovsky
Mohammad Pezeshki
David Lopez-Paz
118
183
0
27 Oct 2021
Robust Contrastive Learning Using Negative Samples with Diminished
  Semantics
Robust Contrastive Learning Using Negative Samples with Diminished Semantics
Songwei Ge
Shlok Kumar Mishra
Haohan Wang
Chun-Liang Li
David Jacobs
SSL
66
71
0
27 Oct 2021
Understanding Dimensional Collapse in Contrastive Self-supervised
  Learning
Understanding Dimensional Collapse in Contrastive Self-supervised Learning
Li Jing
Pascal Vincent
Yann LeCun
Yuandong Tian
SSL
120
359
0
18 Oct 2021
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space
  Perspective
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective
Luca Scimeca
Seong Joon Oh
Sanghyuk Chun
Michael Poli
Sangdoo Yun
OOD
548
54
0
06 Oct 2021
BiaSwap: Removing dataset bias with bias-tailored swapping augmentation
BiaSwap: Removing dataset bias with bias-tailored swapping augmentation
Eungyeup Kim
Jihyeon Janel Lee
Jaegul Choo
77
88
0
23 Aug 2021
Evaluating CLIP: Towards Characterization of Broader Capabilities and
  Downstream Implications
Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications
Sandhini Agarwal
Gretchen Krueger
Jack Clark
Alec Radford
Jong Wook Kim
Miles Brundage
65
143
0
05 Aug 2021
Just Train Twice: Improving Group Robustness without Training Group
  Information
Just Train Twice: Improving Group Robustness without Training Group Information
Emmy Liu
Behzad Haghgoo
Annie S. Chen
Aditi Raghunathan
Pang Wei Koh
Shiori Sagawa
Percy Liang
Chelsea Finn
OOD
107
563
0
19 Jul 2021
Learning Debiased Representation via Disentangled Feature Augmentation
Learning Debiased Representation via Disentangled Feature Augmentation
Jungsoo Lee
Eungyeup Kim
Juyoung Lee
Jihyeon Janel Lee
Jaegul Choo
CML
75
157
0
03 Jul 2021
Can contrastive learning avoid shortcut solutions?
Can contrastive learning avoid shortcut solutions?
Joshua Robinson
Li Sun
Ke Yu
Kayhan Batmanghelich
Stefanie Jegelka
S. Sra
SSL
100
146
0
21 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution
  Generalization?
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang
Kartik Ahuja
Yilun Xu
Yisen Wang
Aaron Courville
OOD
86
96
0
05 Jun 2021
VICReg: Variance-Invariance-Covariance Regularization for
  Self-Supervised Learning
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Adrien Bardes
Jean Ponce
Yann LeCun
SSLDML
153
945
0
11 May 2021
Discover the Unknown Biased Attribute of an Image Classifier
Discover the Unknown Biased Attribute of an Image Classifier
Zhiheng Li
Chenliang Xu
73
50
0
29 Apr 2021
Explaining in Style: Training a GAN to explain a classifier in
  StyleSpace
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Oran Lang
Yossi Gandelsman
Michal Yarom
Yoav Wald
G. Elidan
...
William T. Freeman
Phillip Isola
Amir Globerson
Michal Irani
Inbar Mosseri
GAN
115
154
0
27 Apr 2021
The Low-Rank Simplicity Bias in Deep Networks
The Low-Rank Simplicity Bias in Deep Networks
Minyoung Huh
H. Mobahi
Richard Y. Zhang
Brian Cheung
Pulkit Agrawal
Phillip Isola
105
116
0
18 Mar 2021
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar
Li Jing
Ishan Misra
Yann LeCun
Stéphane Deny
SSL
347
2,368
0
04 Mar 2021
EnD: Entangling and Disentangling deep representations for bias
  correction
EnD: Entangling and Disentangling deep representations for bias correction
Enzo Tartaglione
C. Barbano
Marco Grangetto
78
124
0
02 Mar 2021
Contrastive Learning Inverts the Data Generating Process
Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann
Yash Sharma
Steffen Schneider
Matthias Bethge
Wieland Brendel
SSL
323
223
0
17 Feb 2021
Understanding the Behaviour of Contrastive Loss
Understanding the Behaviour of Contrastive Loss
Feng Wang
Huaping Liu
SSL
111
692
0
15 Dec 2020
Exploring Simple Siamese Representation Learning
Exploring Simple Siamese Representation Learning
Xinlei Chen
Kaiming He
SSL
258
4,076
0
20 Nov 2020
Intriguing Properties of Contrastive Losses
Intriguing Properties of Contrastive Losses
Ting Chen
Calvin Luo
Lala Li
72
177
0
05 Nov 2020
Understanding the Failure Modes of Out-of-Distribution Generalization
Understanding the Failure Modes of Out-of-Distribution Generalization
Vaishnavh Nagarajan
Anders Andreassen
Behnam Neyshabur
OODOODD
71
177
0
29 Oct 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
684
41,563
0
22 Oct 2020
On the surprising similarities between supervised and self-supervised
  models
On the surprising similarities between supervised and self-supervised models
Robert Geirhos
Kantharaju Narayanappa
Benjamin Mitzkus
Matthias Bethge
Felix Wichmann
Wieland Brendel
OODSSLDRL
125
48
0
16 Oct 2020
Are all negatives created equal in contrastive instance discrimination?
Are all negatives created equal in contrastive instance discrimination?
Tiffany Cai
Jonathan Frankle
D. Schwab
Ari S. Morcos
SSL
69
83
0
13 Oct 2020
Large-Scale Methods for Distributionally Robust Optimization
Large-Scale Methods for Distributionally Robust Optimization
Daniel Levy
Y. Carmon
John C. Duchi
Aaron Sidford
81
217
0
12 Oct 2020
Contrastive Learning with Hard Negative Samples
Contrastive Learning with Hard Negative Samples
Joshua Robinson
Ching-Yao Chuang
S. Sra
Stefanie Jegelka
SSL
150
788
0
09 Oct 2020
What shapes feature representations? Exploring datasets, architectures,
  and training
What shapes feature representations? Exploring datasets, architectures, and training
Katherine L. Hermann
Andrew Kyle Lampinen
OOD
91
157
0
22 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks
The Pitfalls of Simplicity Bias in Neural Networks
Harshay Shah
Kaustav Tamuly
Aditi Raghunathan
Prateek Jain
Praneeth Netrapalli
AAML
72
364
0
13 Jun 2020
Understanding Contrastive Representation Learning through Alignment and
  Uniformity on the Hypersphere
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang
Phillip Isola
SSL
164
1,860
0
20 May 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Noam Razin
Nadav Cohen
76
156
0
13 May 2020
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
195
383
0
09 May 2020
Supervised Contrastive Learning
Supervised Contrastive Learning
Prannay Khosla
Piotr Teterwak
Chen Wang
Aaron Sarna
Yonglong Tian
Phillip Isola
Aaron Maschinot
Ce Liu
Dilip Krishnan
SSL
181
4,580
0
23 Apr 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
393
18,897
0
13 Feb 2020
Towards Fairness in Visual Recognition: Effective Strategies for Bias
  Mitigation
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation
Zeyu Wang
Klint Qinami
Yannis Karakozis
Kyle Genova
P. Nair
Kenji Hata
Olga Russakovsky
83
364
0
26 Nov 2019
Distributionally Robust Neural Networks for Group Shifts: On the
  Importance of Regularization for Worst-Case Generalization
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa
Pang Wei Koh
Tatsunori B. Hashimoto
Percy Liang
OOD
108
1,249
0
20 Nov 2019
Learning De-biased Representations with Biased Representations
Learning De-biased Representations with Biased Representations
Hyojin Bahng
Sanghyuk Chun
Sangdoo Yun
Jaegul Choo
Seong Joon Oh
OOD
406
282
0
07 Oct 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
203
2,246
0
05 Jul 2019
Implicit Regularization in Deep Matrix Factorization
Implicit Regularization in Deep Matrix Factorization
Sanjeev Arora
Nadav Cohen
Wei Hu
Yuping Luo
AI4CE
99
509
0
31 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and
  Perturbations
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks
Thomas G. Dietterich
OODVLM
196
3,458
0
28 Mar 2019
Learning Robust Representations by Projecting Superficial Statistics Out
Learning Robust Representations by Projecting Superficial Statistics Out
Haohan Wang
Zexue He
Zachary Chase Lipton
Eric Xing
OOD
73
237
0
02 Mar 2019
Learning Not to Learn: Training Deep Neural Networks with Biased Data
Learning Not to Learn: Training Deep Neural Networks with Biased Data
Byungju Kim
Hyunwoo Kim
Kyungsu Kim
Sungjin Kim
Junmo Kim
OOD
62
411
0
26 Dec 2018
ImageNet-trained CNNs are biased towards texture; increasing shape bias
  improves accuracy and robustness
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos
Patricia Rubisch
Claudio Michaelis
Matthias Bethge
Felix Wichmann
Wieland Brendel
143
2,676
0
29 Nov 2018
Representation Learning with Contrastive Predictive Coding
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord
Yazhe Li
Oriol Vinyals
DRLSSL
356
10,369
0
10 Jul 2018
On the Spectral Bias of Neural Networks
On the Spectral Bias of Neural Networks
Nasim Rahaman
A. Baratin
Devansh Arpit
Felix Dräxler
Min Lin
Fred Hamprecht
Yoshua Bengio
Aaron Courville
161
1,456
0
22 Jun 2018
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