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Last Layer Re-Training is Sufficient for Robustness to Spurious
  Correlations

Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations

6 April 2022
Polina Kirichenko
Pavel Izmailov
A. Wilson
    OOD
ArXivPDFHTML

Papers citing "Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations"

38 / 238 papers shown
Title
Malign Overfitting: Interpolation Can Provably Preclude Invariance
Malign Overfitting: Interpolation Can Provably Preclude Invariance
Yoav Wald
G. Yona
Uri Shalit
Y. Carmon
17
5
0
28 Nov 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
27
10
0
28 Nov 2022
Invariant Learning via Diffusion Dreamed Distribution Shifts
Invariant Learning via Diffusion Dreamed Distribution Shifts
Priyatham Kattakinda
Alexander Levine
S. Feizi
DiffM
23
10
0
18 Nov 2022
Mechanistic Mode Connectivity
Mechanistic Mode Connectivity
Ekdeep Singh Lubana
Eric J. Bigelow
Robert P. Dick
David M. Krueger
Hidenori Tanaka
32
45
0
15 Nov 2022
Elastic Weight Consolidation Improves the Robustness of Self-Supervised
  Learning Methods under Transfer
Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer
Andrius Ovsianas
Jason Ramapuram
Dan Busbridge
Eeshan Gunesh Dhekane
Russ Webb
18
4
0
28 Oct 2022
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Yoonho Lee
Annie S. Chen
Fahim Tajwar
Ananya Kumar
Huaxiu Yao
Percy Liang
Chelsea Finn
OOD
58
197
0
20 Oct 2022
On Feature Learning in the Presence of Spurious Correlations
On Feature Learning in the Presence of Spurious Correlations
Pavel Izmailov
Polina Kirichenko
Nate Gruver
A. Wilson
34
117
0
20 Oct 2022
Freeze then Train: Towards Provable Representation Learning under
  Spurious Correlations and Feature Noise
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise
Haotian Ye
James Zou
Linjun Zhang
OOD
33
21
0
20 Oct 2022
Self-supervised debiasing using low rank regularization
Self-supervised debiasing using low rank regularization
Geon Yeong Park
Chanyong Jung
Sangmin Lee
Jong Chul Ye
Sang Wan Lee
CML
SSL
36
3
0
11 Oct 2022
On Background Bias in Deep Metric Learning
On Background Bias in Deep Metric Learning
Konstantin Kobs
Andreas Hotho
22
1
0
04 Oct 2022
Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in
  Neural Networks
Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks
Sravanti Addepalli
Anshul Nasery
R. Venkatesh Babu
Praneeth Netrapalli
Prateek Jain
AAML
38
3
0
04 Oct 2022
Nuisances via Negativa: Adjusting for Spurious Correlations via Data
  Augmentation
Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation
A. Puli
Nitish Joshi
Yoav Wald
Hera Y. He
Rajesh Ranganath
40
16
0
04 Oct 2022
Explicit Tradeoffs between Adversarial and Natural Distributional
  Robustness
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness
Mazda Moayeri
Kiarash Banihashem
S. Feizi
OOD
75
21
0
15 Sep 2022
Take One Gram of Neural Features, Get Enhanced Group Robustness
Take One Gram of Neural Features, Get Enhanced Group Robustness
Simon Roburin
Charles Corbière
Gilles Puy
Nicolas Thome
Matthieu Aubry
Renaud Marlet
Patrick Pérez
OOD
19
0
0
26 Aug 2022
DAFT: Distilling Adversarially Fine-tuned Models for Better OOD
  Generalization
DAFT: Distilling Adversarially Fine-tuned Models for Better OOD Generalization
Anshul Nasery
Sravanti Addepalli
Praneeth Netrapalli
Prateek Jain
OOD
FedML
39
1
0
19 Aug 2022
Repeated Environment Inference for Invariant Learning
Repeated Environment Inference for Invariant Learning
Aayush Mishra
Anqi Liu
BDL
OOD
28
0
0
26 Jul 2022
Exploring the Design of Adaptation Protocols for Improved Generalization
  and Machine Learning Safety
Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety
Puja Trivedi
Danai Koutra
Jayaraman J. Thiagarajan
AAML
28
0
0
26 Jul 2022
Contrastive Adapters for Foundation Model Group Robustness
Contrastive Adapters for Foundation Model Group Robustness
Michael Zhang
Christopher Ré
VLM
18
61
0
14 Jul 2022
Predicting is not Understanding: Recognizing and Addressing
  Underspecification in Machine Learning
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning
Damien Teney
Maxime Peyrard
Ehsan Abbasnejad
35
29
0
06 Jul 2022
Guillotine Regularization: Why removing layers is needed to improve
  generalization in Self-Supervised Learning
Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning
Florian Bordes
Randall Balestriero
Q. Garrido
Adrien Bardes
Pascal Vincent
32
22
0
27 Jun 2022
Understanding Robust Learning through the Lens of Representation
  Similarities
Understanding Robust Learning through the Lens of Representation Similarities
Christian Cianfarani
A. Bhagoji
Vikash Sehwag
Ben Y. Zhao
Prateek Mittal
Haitao Zheng
OOD
21
16
0
20 Jun 2022
How Robust is Unsupervised Representation Learning to Distribution
  Shift?
How Robust is Unsupervised Representation Learning to Distribution Shift?
Yuge Shi
Imant Daunhawer
Julia E. Vogt
Philip H. S. Torr
Amartya Sanyal
OOD
32
25
0
17 Jun 2022
Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion
  Classification
Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification
Adriano Lucieri
Fabian Schmeisser
Christoph Balada
Shoaib Ahmed Siddiqui
Andreas Dengel
Sheraz Ahmed
17
3
0
13 Jun 2022
Feature Space Particle Inference for Neural Network Ensembles
Feature Space Particle Inference for Neural Network Ensembles
Shingo Yashima
Teppei Suzuki
Kohta Ishikawa
Ikuro Sato
Rei Kawakami
BDL
14
11
0
02 Jun 2022
Why does Throwing Away Data Improve Worst-Group Error?
Why does Throwing Away Data Improve Worst-Group Error?
Kamalika Chaudhuri
Kartik Ahuja
Martín Arjovsky
David Lopez-Paz
28
15
0
23 May 2022
Diverse Weight Averaging for Out-of-Distribution Generalization
Diverse Weight Averaging for Out-of-Distribution Generalization
Alexandre Ramé
Matthieu Kirchmeyer
Thibaud Rahier
A. Rakotomamonjy
Patrick Gallinari
Matthieu Cord
OOD
199
128
0
19 May 2022
Unraveling Attention via Convex Duality: Analysis and Interpretations of
  Vision Transformers
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers
Arda Sahiner
Tolga Ergen
Batu Mehmet Ozturkler
John M. Pauly
Morteza Mardani
Mert Pilanci
34
33
0
17 May 2022
Improved Group Robustness via Classifier Retraining on Independent
  Splits
Improved Group Robustness via Classifier Retraining on Independent Splits
Thien Hai Nguyen
Hongyang R. Zhang
Huy Le Nguyen
OOD
31
2
0
20 Apr 2022
Geodesic Multi-Modal Mixup for Robust Fine-Tuning
Geodesic Multi-Modal Mixup for Robust Fine-Tuning
Changdae Oh
Junhyuk So
Hoyoon Byun
Yongtaek Lim
Minchul Shin
Jong-June Jeon
Kyungwoo Song
33
26
0
08 Mar 2022
Diversify and Disambiguate: Learning From Underspecified Data
Diversify and Disambiguate: Learning From Underspecified Data
Yoonho Lee
Huaxiu Yao
Chelsea Finn
213
64
0
07 Feb 2022
Controlling Directions Orthogonal to a Classifier
Controlling Directions Orthogonal to a Classifier
Yilun Xu
Hao He
T. Shen
Tommi Jaakkola
61
19
0
27 Jan 2022
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic
  Time
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time
Zhao-quan Song
Licheng Zhang
Ruizhe Zhang
23
64
0
14 Dec 2021
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
305
7,443
0
11 Nov 2021
Learning to Estimate Without Bias
Learning to Estimate Without Bias
Niv Nayman
Rong Jin
Lihi Zelnik-Manor
11
12
0
24 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
384
49
0
06 Oct 2021
Recent Advances of Continual Learning in Computer Vision: An Overview
Recent Advances of Continual Learning in Computer Vision: An Overview
Haoxuan Qu
Hossein Rahmani
Li Xu
Bryan M. Williams
Jun Liu
VLM
CLL
25
73
0
23 Sep 2021
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David M. Krueger
Ethan Caballero
J. Jacobsen
Amy Zhang
Jonathan Binas
Dinghuai Zhang
Rémi Le Priol
Aaron Courville
OOD
215
901
0
02 Mar 2020
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,084
0
24 Oct 2016
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