Heterogeneity: opportunities for causal inference and prediction
Seminar | October 4 | 4-5 p.m. | 1011 Evans Hall
Peter Bühlmann, ETH Zürich
Heterogeneity in potentially large-scale data can be beneficially exploited for causal inference and more robust prediction. The key idea relies on invariance and stability across different heterogeneous regimes or sub-populations. What we term as "anchor regression" opens some novel insights and connections between causality and protection (robustness) against worst case interventions in prediction problems. The resulting new procedures offer (possibly conservative) confidence guarantees. We will discuss the methodology as well as some applications.