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UMIX: Improving Importance Weighting for Subpopulation Shift via
  Uncertainty-Aware Mixup

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

19 September 2022
Zongbo Han
Zhipeng Liang
Fan Yang
Liu Liu
Lanqing Li
Yatao Bian
P. Zhao
Bing Wu
Changqing Zhang
Jianhua Yao
ArXivPDFHTML

Papers citing "UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup"

8 / 8 papers shown
Title
Understanding Why Generalized Reweighting Does Not Improve Over ERM
Understanding Why Generalized Reweighting Does Not Improve Over ERM
Runtian Zhai
Chen Dan
Zico Kolter
Pradeep Ravikumar
OOD
31
27
0
28 Jan 2022
Iterative Distillation for Better Uncertainty Estimates in Multitask
  Emotion Recognition
Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognition
Didan Deng
Liang Wu
Bertram E. Shi
39
32
0
21 Jul 2021
Gradient Matching for Domain Generalization
Gradient Matching for Domain Generalization
Yuge Shi
Jeffrey S. Seely
Philip H. S. Torr
Siddharth Narayanaswamy
Awni Y. Hannun
Nicolas Usunier
Gabriel Synnaeve
OOD
202
246
0
20 Apr 2021
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
128
368
0
09 May 2020
Dropout: Explicit Forms and Capacity Control
Dropout: Explicit Forms and Capacity Control
R. Arora
Peter L. Bartlett
Poorya Mianjy
Nathan Srebro
42
33
0
06 Mar 2020
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
212
888
0
02 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
4,940
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
243
9,042
0
06 Jun 2015
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