Heterogeneity: opportunities for causal inference and prediction

Neyman Seminar
Oct 4, 2017 4:00pm to 5:00pm
1011 Evans Hall
Happening As Scheduled
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 ...
Peter Bühlmann, ETH Zürich