Annotation-Free Group Robustness via Loss-Based Resampling

8 December 2023

Papers citing "Annotation-Free Group Robustness via Loss-Based Resampling"

9 / 9 papers shown

Title
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations Polina Kirichenko Pavel Izmailov A. Wilson OOD 76 333 0 06 Apr 2022
BARACK: Partially Supervised Group Robustness With Guarantees N. Sohoni Maziar Sanjabi Nicolas Ballas Aditya Grover Shaoliang Nie Hamed Firooz Christopher Ré OOD 59 24 0 31 Dec 2021
Salient ImageNet: How to discover spurious features in Deep Learning? Sahil Singla Soheil Feizi AAML VLM 60 120 0 08 Oct 2021
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 82 557 0 19 Jul 2021
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems N. Sohoni Jared A. Dunnmon Geoffrey Angus Albert Gu Christopher Ré 63 249 0 25 Nov 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 57 382 0 14 Oct 2020
Learning from Failure: Training Debiased Classifier from Biased Classifier J. Nam Hyuntak Cha SungSoo Ahn Jaeho Lee Jinwoo Shin 57 148 0 06 Jul 2020
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 83 1,234 0 20 Nov 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 295 2,109 0 24 Oct 2016