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Farzin Ghaffarizadeh

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Research Papers

Improve User Retention with Causal Learning

S. Du, J. Lee, F. Ghaffarizadeh
User retention is a key focus for consumer based internet companies and promotions are an effective lever to improve retention. However, companies rely either on non-causal churn prediction to capture heterogeneity or on regular A/B testing to capture average treatment effect. In this paper, we propose a heterogeneous treatment effect optimization framework to capture both heterogeneity and causal effect. [...] [PDF]
SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019

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