Personalization and Optimization of Decision Parameters via Heterogenous Causal Effects

29 Jan 2019Ye TuKinjal BasuJinyun YanBirjodh TiwanaShaunak Chatterjee

Randomized experimentation (also known as A/B testing or bucket testing) is very commonly used in the internet industry to measure the effect of a new treatment. Often, the decision on the basis of such A/B testing is to ramp the treatment variant that did best for the entire population... (read more)

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