ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2007.02561
  4. Cited By
Learning from Failure: Training Debiased Classifier from Biased
  Classifier

Learning from Failure: Training Debiased Classifier from Biased Classifier

6 July 2020
J. Nam
Hyuntak Cha
SungSoo Ahn
Jaeho Lee
Jinwoo Shin
ArXivPDFHTML

Papers citing "Learning from Failure: Training Debiased Classifier from Biased Classifier"

48 / 48 papers shown
Title
Are We Done with Object-Centric Learning?
Are We Done with Object-Centric Learning?
Alexander Rubinstein
Ameya Prabhu
Matthias Bethge
Seong Joon Oh
OCL
745
0
0
09 Apr 2025
Sebra: Debiasing Through Self-Guided Bias Ranking
Sebra: Debiasing Through Self-Guided Bias Ranking
Adarsh Kappiyath
Abhra Chaudhuri
Ajay Jaiswal
Ziquan Liu
Yunpeng Li
Xiatian Zhu
L. Yin
CML
230
1
1
30 Jan 2025
UnLearning from Experience to Avoid Spurious Correlations
UnLearning from Experience to Avoid Spurious Correlations
Jeff Mitchell
Jesús Martínez del Rincón
Niall McLaughlin
43
0
0
04 Sep 2024
Language-guided Detection and Mitigation of Unknown Dataset Bias
Language-guided Detection and Mitigation of Unknown Dataset Bias
Zaiying Zhao
Soichiro Kumano
Toshihiko Yamasaki
53
2
0
05 Jun 2024
Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables
Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables
James Hinns
David Martens
54
2
0
24 May 2024
Enhancing Intrinsic Features for Debiasing via Investigating
  Class-Discerning Common Attributes in Bias-Contrastive Pair
Enhancing Intrinsic Features for Debiasing via Investigating Class-Discerning Common Attributes in Bias-Contrastive Pair
Jeonghoon Park
Chaeyeon Chung
Juyoung Lee
Jaegul Choo
42
3
0
30 Apr 2024
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
Samuel Marks
Can Rager
Eric J. Michaud
Yonatan Belinkov
David Bau
Aaron Mueller
53
122
0
28 Mar 2024
Does Invariant Graph Learning via Environment Augmentation Learn
  Invariance?
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
Yongqiang Chen
Yatao Bian
Kaiwen Zhou
Binghui Xie
Bo Han
James Cheng
OOD
45
34
0
29 Oct 2023
FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
Yupei Du
Albert Gatt
Dong Nguyen
36
1
0
10 Oct 2023
Confidence-Based Model Selection: When to Take Shortcuts for
  Subpopulation Shifts
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts
Annie S. Chen
Yoonho Lee
Amrith Rajagopal Setlur
Sergey Levine
Chelsea Finn
OOD
27
5
0
19 Jun 2023
Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization
Modeling the Q-Diversity in a Min-max Play Game for Robust Optimization
Ting Wu
Rui Zheng
Tao Gui
Qi Zhang
Xuanjing Huang
53
2
0
20 May 2023
Overwriting Pretrained Bias with Finetuning Data
Overwriting Pretrained Bias with Finetuning Data
Angelina Wang
Olga Russakovsky
31
30
0
10 Mar 2023
Differentially Private Neural Tangent Kernels for Privacy-Preserving
  Data Generation
Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation
Yilin Yang
Kamil Adamczewski
Danica J. Sutherland
Xiaoxiao Li
Mijung Park
38
14
0
03 Mar 2023
Delving into Identify-Emphasize Paradigm for Combating Unknown Bias
Delving into Identify-Emphasize Paradigm for Combating Unknown Bias
Bowen Zhao
Chen Chen
Qian-Wei Wang
Anfeng He
Shutao Xia
47
1
0
22 Feb 2023
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating
  Orthogonal Features
Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features
Annie S. Chen
Yoonho Lee
Amrith Rajagopal Setlur
Sergey Levine
Chelsea Finn
VLM
40
9
0
10 Feb 2023
Hyper-parameter Tuning for Fair Classification without Sensitive
  Attribute Access
Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access
A. Veldanda
Ivan Brugere
Sanghamitra Dutta
Alan Mishler
S. Garg
47
5
0
02 Feb 2023
Model Agnostic Sample Reweighting for Out-of-Distribution Learning
Model Agnostic Sample Reweighting for Out-of-Distribution Learning
Xiao Zhou
Yong Lin
Renjie Pi
Weizhong Zhang
Renzhe Xu
Peng Cui
Tong Zhang
OODD
44
61
0
24 Jan 2023
Look Beyond Bias with Entropic Adversarial Data Augmentation
Look Beyond Bias with Entropic Adversarial Data Augmentation
Thomas Duboudin
Emmanuel Dellandrea
Corentin Abgrall
Gilles Hénaff
Liming Chen
CML
38
4
0
10 Jan 2023
Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases
Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases
Mazda Moayeri
Wenxiao Wang
Sahil Singla
S. Feizi
73
14
0
05 Dec 2022
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers
Wanqian Yang
Polina Kirichenko
Micah Goldblum
A. Wilson
DRL
30
10
0
28 Nov 2022
Information Removal at the bottleneck in Deep Neural Networks
Information Removal at the bottleneck in Deep Neural Networks
Enzo Tartaglione
56
2
0
30 Sep 2022
Distilling Model Failures as Directions in Latent Space
Distilling Model Failures as Directions in Latent Space
Saachi Jain
Hannah Lawrence
Ankur Moitra
Aleksander Madry
23
90
0
29 Jun 2022
Revisiting the Importance of Amplifying Bias for Debiasing
Revisiting the Importance of Amplifying Bias for Debiasing
Jungsoo Lee
Jeonghoon Park
Daeyoung Kim
Juyoung Lee
Edward Choi
Jaegul Choo
57
22
0
29 May 2022
Learning to Split for Automatic Bias Detection
Learning to Split for Automatic Bias Detection
Yujia Bao
Regina Barzilay
26
20
0
28 Apr 2022
Unsupervised Learning of Unbiased Visual Representations
Unsupervised Learning of Unbiased Visual Representations
C. Barbano
Enzo Tartaglione
Marco Grangetto
SSL
CML
OOD
41
1
0
26 Apr 2022
The Two Dimensions of Worst-case Training and the Integrated Effect for
  Out-of-domain Generalization
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization
Zeyi Huang
Haohan Wang
Dong Huang
Yong Jae Lee
Eric P. Xing
21
22
0
09 Apr 2022
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
Robik Shrestha
Kushal Kafle
Christopher Kanan
CML
38
13
0
05 Apr 2022
Improving the Fairness of Chest X-ray Classifiers
Improving the Fairness of Chest X-ray Classifiers
Haoran Zhang
Natalie Dullerud
Karsten Roth
Lauren Oakden-Rayner
Stephen R. Pfohl
Marzyeh Ghassemi
23
65
0
23 Mar 2022
NeuroView-RNN: It's About Time
NeuroView-RNN: It's About Time
C. Barberan
Sina Alemohammad
Naiming Liu
Randall Balestriero
Richard G. Baraniuk
AI4TS
HAI
41
2
0
23 Feb 2022
Controlling Directions Orthogonal to a Classifier
Controlling Directions Orthogonal to a Classifier
Yilun Xu
Hao He
T. Shen
Tommi Jaakkola
65
19
0
27 Jan 2022
Measure and Improve Robustness in NLP Models: A Survey
Measure and Improve Robustness in NLP Models: A Survey
Xuezhi Wang
Haohan Wang
Diyi Yang
139
131
0
15 Dec 2021
Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data
  via Generative Bias-transformation
Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
Yeonsung Jung
Hajin Shim
J. Yang
Eunho Yang
34
8
0
02 Dec 2021
Toward Learning Human-aligned Cross-domain Robust Models by Countering
  Misaligned Features
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features
Haohan Wang
Zeyi Huang
Hanlin Zhang
Yong Jae Lee
Eric P. Xing
OOD
138
16
0
05 Nov 2021
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
56
173
0
27 Oct 2021
An Evaluation Dataset and Strategy for Building Robust Multi-turn
  Response Selection Model
An Evaluation Dataset and Strategy for Building Robust Multi-turn Response Selection Model
Kijong Han
Seojin Lee
Wooin Lee
Joosung Lee
Donghun Lee
AAML
25
5
0
10 Sep 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
32
87
0
23 Aug 2021
Unsupervised Learning of Debiased Representations with Pseudo-Attributes
Unsupervised Learning of Debiased Representations with Pseudo-Attributes
Seonguk Seo
Joon-Young Lee
Bohyung Han
FaML
76
48
0
06 Aug 2021
Just Train Twice: Improving Group Robustness without Training Group
  Information
Just Train Twice: Improving Group Robustness without Training Group Information
E. Liu
Behzad Haghgoo
Annie S. Chen
Aditi Raghunathan
Pang Wei Koh
Shiori Sagawa
Percy Liang
Chelsea Finn
OOD
37
540
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
19
150
0
03 Jul 2021
Fairness via Representation Neutralization
Fairness via Representation Neutralization
Mengnan Du
Subhabrata Mukherjee
Guanchu Wang
Ruixiang Tang
Ahmed Hassan Awadallah
Xia Hu
30
78
0
23 Jun 2021
Learning Stable Classifiers by Transferring Unstable Features
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao
Shiyu Chang
Regina Barzilay
OOD
32
8
0
15 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
30
95
0
05 Jun 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers
  Solutions with Superior OOD Generalization
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Damien Teney
Ehsan Abbasnejad
Simon Lucey
Anton Van Den Hengel
53
87
0
12 May 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
26
123
0
02 Mar 2021
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural
  Networks
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks
L. N. Darlow
Stanisław Jastrzębski
Amos Storkey
48
24
0
19 Nov 2020
Gradient Starvation: A Learning Proclivity in Neural Networks
Gradient Starvation: A Learning Proclivity in Neural Networks
Mohammad Pezeshki
Sekouba Kaba
Yoshua Bengio
Aaron Courville
Doina Precup
Guillaume Lajoie
MLT
54
259
0
18 Nov 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
358
4,237
0
23 Aug 2019
Improving fairness in machine learning systems: What do industry
  practitioners need?
Improving fairness in machine learning systems: What do industry practitioners need?
Kenneth Holstein
Jennifer Wortman Vaughan
Hal Daumé
Miroslav Dudík
Hanna M. Wallach
FaML
HAI
195
742
0
13 Dec 2018
1