1 code implementation • 29 Feb 2024 • Benjamin Cohen-Wang, Joshua Vendrow, Aleksander Madry
In particular, we focus on two possible failure modes of models under distribution shift: poor extrapolation (e. g., they cannot generalize to a different domain) and biases in the training data (e. g., they rely on spurious features).
1 code implementation • 3 Mar 2021 • Mayee F. Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Ré
We apply our decomposition framework to three scenarios -- well-specified, misspecified, and corrected models -- to 1) choose between labeled and unlabeled data and 2) learn from their combination.
