3 papers
stat.ML2024
FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality
Sai Li, Linjun Zhang
Machine learning methods often assume that the test data have the same distribution as the training data. However, this assumption may not hold due to multiple levels of heterogene…
stat.ME2023
Multi-dimensional domain generalization with low-rank structures
Sai Li, Linjun Zhang
In conventional statistical and machine learning methods, it is typically assumed that the test data are identically distributed with the training data. However, this assumption do…
cs.LG2023
HappyMap: A Generalized Multi-calibration Method
Zhun Deng, Cynthia Dwork, Linjun Zhang
Multi-calibration is a powerful and evolving concept originating in the field of algorithmic fairness. For a predictor that estimates the outcome given covariates , and…