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cs.LG2024
Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
Monica Welfert, Nathan Stromberg, Lalitha Sankar
Ensuring fair predictions across many distinct subpopulations in the training data can be prohibitive for large models. Recently, simple linear last layer retraining strategies, in…
cs.LG2024
Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains
Nathan Stromberg, Rohan Ayyagari, Monica Welfert +3
Existing methods for last layer retraining that aim to optimize worst-group accuracy (WGA) rely heavily on well-annotated groups in the training data. We show, both in theory and p…