Boosting Test Performance with Importance Sampling--a Subpopulation Perspective
Despite empirical risk minimization (ERM) is widely applied in the machine learning
community, its performance is limited on data with spurious correlation or subpopulation that …
community, its performance is limited on data with spurious correlation or subpopulation that …
Optimizing importance weighting in the presence of sub-population shifts
A distribution shift between the training and test data can severely harm performance of
machine learning models. Importance weighting addresses this issue by assigning different …
machine learning models. Importance weighting addresses this issue by assigning different …