Search Results for author:
Found 2 papers, 1 papers with code
Exchanging Lessons Between Algorithmic Fairness and Domain Generalization
Developing learning approaches that are not overly sensitive to the training distribution is central to research on domain- or out-of-distribution generalization, robust optimization and fairness.
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Distributional shift is one of the major obstacles when transferring machine learning prediction systems from the lab to the real world.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
