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Examining and Combating Spurious Features under Distribution Shift

ICML 2021 · Label-efficient and robust learning › Recognition and long-tail · approach: Data augmentation and generalization bias · 13 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use instance-level weights within groups in addition to group-level weights (GC-DRO instead of group DRO)CelebA with imperfect partitions · CelebA imperfect partitionrobust accuracy: 45.97 $\pm$ 1.73 -> 82.85 $\pm$ 1.54Helped
Use instance-level weights within groups in addition to group-level weights (GC-DRO instead of group DRO)MNLI with imperfect partitions · MNLI imperfect partitionrobust accuracy: 70.34 $\pm$ 2.19 -> 75.32 $\pm$ 0.93Helped
Use instance-level weights within groups in addition to group-level weights (GC-DRO instead of group DRO)FDCL18 with imperfect partitions · FDCL18 imperfect partitionrobust accuracy: 36.24 $\pm$ 3.80 -> 48.42 $\pm$ 6.72Helped
Use instance-level weights within groups in addition to group-level weights (GC-DRO instead of group DRO)FDCL18 with unsupervised-cluster partitions · FDCL18 unsupervised clusteringrobust accuracy: 34.48 $\pm$ 4.69 -> 45.06 $\pm$ 6.77Helped
Use GC-DRO rather than ERMCelebA with clean partitions · CelebA clean partitionrobust accuracy: 40.14 $\pm$ 0.99 -> 88.75 $\pm$ 0.82Helped
Use GC-DRO rather than group DRO (EG)MNLI with clean partitions · MNLI clean partitionrobust accuracy: 77.88 $\pm$ 1.36 -> 77.82 $\pm$ 1.45No clear effect
Use GC-DRO rather than ERMFDCL18 with clean partitions · FDCL18 clean partitionrobust accuracy: 34.30 $\pm$ 1.83 -> 57.28 $\pm$ 2.71Helped
Use GC-DRO rather than the best average-accuracy baselineCelebA with imperfect partitions · CelebA imperfect partitionaverage accuracy: 95.92 $\pm$ 0.05 -> 89.32 $\pm$ 2.21Hurt
Use GC-DRO rather than the best average-accuracy baselineFDCL18 with imperfect partitions · FDCL18 imperfect partitionaverage accuracy: 80.66 $\pm$ 0.52 -> 72.02 $\pm$ 2.96Hurt
Vary alpha and beta; under clean partitions, use larger beta and smaller alpha (ablation)GC-DRO on MNLI · MNLI clean and imperfect partitionsrobust accuracyMixed

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