A Large Scale Heterogeneous Treatment Effect Estimation Framework and Its Applications of Users' Journey at Snap
大规模异质性处理效应估计框架及其在 Snap 用户历程中的应用
Heterogeneous Treatment Effect (HTE) and Conditional Average Treatment Effect (CATE) models relax the assumption that treatment effects are the same for every user. We present a large scale industrial framework for estimating HTE using experimental data from hundreds of millions of Snapchat users. By combining results across many experiments, the framework uncovers latent user characteristics that were previously unmeasurable and produces stable treatment effect estimates at…