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Found 3 papers, 2 papers with code
Generalized Causal Tree for Uplift Modeling
In this paper, we propose a generalization of tree-based approaches to tackle multiple discrete and continuous-valued treatments.
Feedback Shaping: A Modeling Approach to Nurture Content Creation
In this work, we propose a modeling approach to predict how feedback from content consumers incentivizes creators.
Personalized Treatment Selection using Causal Heterogeneity
In this work, we develop a framework for personalization through (i) estimation of heterogeneous treatment effect at either a cohort or member-level, followed by (ii) selection of optimal treatment variants for cohorts (or members) obtained through (deterministic or stochastic) constrained optimization.
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