Curriculum-enhanced GroupDRO: Challenging the Norm of Avoiding Curriculum Learning in Subpopulation Shift Setups

Researchers propose Curriculum-enhanced Group Distributionally Robust Optimization (CeGDRO), a new machine learning approach that challenges conventional wisdom by using curriculum learning in subpopulation shift scenarios. The method achieves up to 6.2% improvement over state-of-the-art results on benchmark datasets like Waterbirds by strategically prioritizing hard bias-confirming and easy bias-conflicting samples.