8 citations · 10 across the 3 of their papers we have counts for
3 papers
Evaluating the Robustness of Targeted Maximum Likelihood Estimators via Realistic Simulations in Nutrition Intervention Trials
Haodong Li, Sonali Rosete, Jeremy Coyle +9
Several recently developed methods have the potential to harness machine learning in the pursuit of target quantities inspired by causal inference, including inverse weighting, dou…
Personalized Online Machine Learning
Ivana Malenica, Rachael V. Phillips, Romain Pirracchio +3
In this work, we introduce the Personalized Online Super Learner (POSL) -- an online ensembling algorithm for streaming data whose optimization procedure accommodates varying degre…
Targeting Learning: Robust Statistics for Reproducible Research
Jeremy R. Coyle, Nima S. Hejazi, Ivana Malenica +9
Targeted Learning is a subfield of statistics that unifies advances in causal inference, machine learning and statistical theory to help answer scientifically impactful questions w…