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Model Patching: Closing the Subgroup Performance Gap with Data
  Augmentation

Model Patching: Closing the Subgroup Performance Gap with Data Augmentation

15 August 2020
Karan Goel
Albert Gu
Yixuan Li
Christopher Ré
ArXivPDFHTML

Papers citing "Model Patching: Closing the Subgroup Performance Gap with Data Augmentation"

25 / 25 papers shown
Title
FairDropout: Using Example-Tied Dropout to Enhance Generalization of Minority Groups
Géraldin Nanfack
Eugene Belilovsky
59
0
0
10 Feb 2025
Process Reward Model with Q-Value Rankings
Process Reward Model with Q-Value Rankings
W. Li
Yixuan Li
LRM
59
15
0
15 Oct 2024
Bias Amplification Enhances Minority Group Performance
Bias Amplification Enhances Minority Group Performance
Gaotang Li
Jiarui Liu
Wei Hu
28
5
0
13 Sep 2023
On Counterfactual Data Augmentation Under Confounding
On Counterfactual Data Augmentation Under Confounding
Abbavaram Gowtham Reddy
Saketh Bachu
Saloni Dash
Charchit Sharma
Amit Sharma
V. Balasubramanian
CML
BDL
33
0
0
29 May 2023
Rectifying Group Irregularities in Explanations for Distribution Shift
Rectifying Group Irregularities in Explanations for Distribution Shift
Adam Stein
Yinjun Wu
Eric Wong
Mayur Naik
34
1
0
25 May 2023
$Δ$-Patching: A Framework for Rapid Adaptation of Pre-trained
  Convolutional Networks without Base Performance Loss
ΔΔΔ-Patching: A Framework for Rapid Adaptation of Pre-trained Convolutional Networks without Base Performance Loss
Chaitanya Devaguptapu
Samarth Sinha
K. J. Joseph
V. Balasubramanian
Animesh Garg
65
1
0
26 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
36
1
0
22 Feb 2023
Editing Models with Task Arithmetic
Editing Models with Task Arithmetic
Gabriel Ilharco
Marco Tulio Ribeiro
Mitchell Wortsman
Suchin Gururangan
Ludwig Schmidt
Hannaneh Hajishirzi
Ali Farhadi
KELM
MoMe
MU
72
435
0
08 Dec 2022
Data Models for Dataset Drift Controls in Machine Learning With Optical
  Images
Data Models for Dataset Drift Controls in Machine Learning With Optical Images
Luis Oala
Marco Aversa
Gabriel Nobis
Kurt Willis
Yoan Neuenschwander
...
E. Pomarico
Wojciech Samek
Roderick Murray-Smith
Christoph Clausen
B. Sanguinetti
28
5
0
04 Nov 2022
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
35
13
0
11 Oct 2022
Equivariant Disentangled Transformation for Domain Generalization under
  Combination Shift
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift
Yivan Zhang
Jindong Wang
Xingxu Xie
Masashi Sugiyama
OOD
42
1
0
03 Aug 2022
Transferring Fairness under Distribution Shifts via Fair Consistency
  Regularization
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization
Bang An
Zora Che
Mucong Ding
Furong Huang
19
31
0
26 Jun 2022
Perfectly Balanced: Improving Transfer and Robustness of Supervised
  Contrastive Learning
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
Mayee F. Chen
Daniel Y. Fu
A. Narayan
Michael Zhang
Zhao Song
Kayvon Fatahalian
Christopher Ré
SSL
32
47
0
15 Apr 2022
BARACK: Partially Supervised Group Robustness With Guarantees
BARACK: Partially Supervised Group Robustness With Guarantees
N. Sohoni
Maziar Sanjabi
Nicolas Ballas
Aditya Grover
Shaoliang Nie
Hamed Firooz
Christopher Ré
OOD
20
24
0
31 Dec 2021
The Effect of Model Size on Worst-Group Generalization
The Effect of Model Size on Worst-Group Generalization
Alan Pham
Eunice Chan
V. Srivatsa
Dhruba Ghosh
Yaoqing Yang
Yaodong Yu
Ruiqi Zhong
Joseph E. Gonzalez
Jacob Steinhardt
23
5
0
08 Dec 2021
Focus on the Common Good: Group Distributional Robustness Follows
Focus on the Common Good: Group Distributional Robustness Follows
Vihari Piratla
Praneeth Netrapalli
Sunita Sarawagi
OOD
28
25
0
06 Oct 2021
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for
  Pre-training Debiasing
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing
Sindhu C. M. Gowda
Shalmali Joshi
Haoran Zhang
Marzyeh Ghassemi
CML
32
8
0
27 Aug 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
27
86
0
23 Aug 2021
Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding
  Ecosystems
Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems
Laurel J. Orr
Atindriyo Sanyal
Xiao Ling
Karan Goel
Megan Leszczynski
25
18
0
11 Aug 2021
Out-of-distribution Generalization in the Presence of Nuisance-Induced
  Spurious Correlations
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations
A. Puli
Lily H. Zhang
Eric K. Oermann
Rajesh Ranganath
OOD
OODD
24
48
0
29 Jun 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
OOD
71
1,377
0
14 Dec 2020
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
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
297
10,368
0
12 Dec 2018
Constructing Unrestricted Adversarial Examples with Generative Models
Constructing Unrestricted Adversarial Examples with Generative Models
Yang Song
Rui Shu
Nate Kushman
Stefano Ermon
GAN
AAML
185
302
0
21 May 2018
Conditional Image Synthesis With Auxiliary Classifier GANs
Conditional Image Synthesis With Auxiliary Classifier GANs
Augustus Odena
C. Olah
Jonathon Shlens
GAN
250
3,190
0
30 Oct 2016
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