View publication

*=Equal Contributors

This paper was accepted at the workshop "Trustworthy Machine Learning for Healthcare Workshop" at the conference ICLR 2023.

When analyzing robustness of predictive models under distribution shift, many works focus on tackling generalization in the presence of spurious correlations. In this case, one typically makes use of covariates or environment indicators to enforce independencies in learned models to guarantee generalization under various distribution shifts. In this work, we analyze a class of distribution shifts, where such independencies are not desirable, as there is a causal association between covariates and outcomes of interest. This case is common in the health space where covariates can be causally, as opposed to spuriously, related to outcomes of interest. We formalize this setting and relate it to common distribution shift settings from the literature. We theoretically show why standard supervised learning and invariant learning will not yield robust predictors in this case, while including the causal covariates into the prediction model can recover robustness. We demonstrate our theoretical findings in experiments on both synthetic and real data.

Related readings and updates.

Shift-Curvature, SGD, and Generalization

*= Equal Contributors A longstanding debate surrounds the related hypotheses that low-curvature minima generalize better, and that stochastic gradient descent (SGD) discourages curvature. We offer a more complete and nuanced view in support of both hypotheses. First, we show that curvature harms test performance through two new mechanisms, the shift-curvature and bias-curvature, in addition to a known parameter-covariance mechanism. The shift…
See paper details

A Large-Scale Observational Study of the Causal Effects of a Behavioral Health Nudge

This paper was accepted at the workshop "Causality for Real-world Impact" at NeurIPS 2022. The Apple Watch encourages users to stand throughout the day by delivering a notification onto the users’ wrist if they have been sitting for the first 50 minutes of an hour. This simple behavioral intervention exemplifies the classical definition of nudge as a choice architecture that alters behavior without forbidding options or significantly changing…
See paper details