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cs.LG2025★ 1 cited
FairDropout: Using Example-Tied Dropout to Enhance Generalization of Minority Groups
Geraldin Nanfack, Eugene Belilovsky
Deep learning models frequently exploit spurious features in training data to achieve low training error, often resulting in poor generalization when faced with shifted testing dis…
cs.LG2024
Not Only the Last-Layer Features for Spurious Correlations: All Layer Deep Feature Reweighting
Humza Wajid Hameed, Geraldin Nanfack, Eugene Belilovsky
Spurious correlations are a major source of errors for machine learning models, in particular when aiming for group-level fairness. It has been recently shown that a powerful appro…