Develops CAST, a polynomial-time approximation algorithm for selecting k individuals for HIV treatment in a network to minimize expected transmission cascades, achieving a 2√|P| approximation ratio.
The lancet HIV , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
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A conditional adaptive perturbation approach enables valid in-sample inference for machine learning-identified subgroups with nonregular boundaries via triple robustness.
citing papers explorer
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Network-Based Interventions for HIV Prevention via Cascade-Aware Suppression of Transmission
Develops CAST, a polynomial-time approximation algorithm for selecting k individuals for HIV treatment in a network to minimize expected transmission cascades, achieving a 2√|P| approximation ratio.
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In-Sample Evaluation of Subgroups Identified by Generic Machine Learning
A conditional adaptive perturbation approach enables valid in-sample inference for machine learning-identified subgroups with nonregular boundaries via triple robustness.