27 citations · 110 across the 14 of their papers we have counts for
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stat.ML2016★ 27 cited
Generalized Optimal Matching Methods for Causal Inference
Nathan Kallus
We develop an encompassing framework for matching, covariate balancing, and doubly-robust methods for causal inference from observational data called generalized optimal matching (…
stat.ML2016★ 20 cited
Recursive Partitioning for Personalization using Observational Data
Nathan Kallus
We study the problem of learning to choose from m discrete treatment options (e.g., news item or medical drug) the one with best causal effect for a particular instance (e.g., user…
stat.ME2016★ 20 cited
A Framework for Optimal Matching for Causal Inference
Nathan Kallus
We propose a novel framework for matching estimators for causal effect from observational data that is based on minimizing the dual norm of estimation error when expressed as an op…