6 citations · 12 across the 10 of their papers we have counts for
3 papers · 1 filter
Removing Hidden Confounding by Experimental Grounding
Nathan Kallus, Aahlad Manas Puli, Uri Shalit
Observational data is increasingly used as a means for making individual-level causal predictions and intervention recommendations. The foremost challenge of causal inference from…
Harmonizing Fully Optimal Designs with Classic Randomization in Fixed Trial Experiments
Adam Kapelner, Abba M. Krieger, Uri Shalit +1
There is a movement in design of experiments away from the classic randomization put forward by Fisher, Cochran and others to one based on optimization. In fixed-sample trials comp…
Learning Weighted Representations for Generalization Across Designs
Fredrik D. Johansson, Nathan Kallus, Uri Shalit +1
Predictive models that generalize well under distributional shift are often desirable and sometimes crucial to building robust and reliable machine learning applications. We focus…