Corpus ID: 59413829

Personalization and Optimization of Decision Parameters via Heterogenous Causal Effects

@article{Tu2019PersonalizationAO,
  title={Personalization and Optimization of Decision Parameters via Heterogenous Causal Effects},
  author={Y. Tu and Kinjal Basu and Jinyun Yan and B. Tiwana and Shaunak Chatterjee},
  journal={ArXiv},
  year={2019},
  volume={abs/1901.10550}
}
  • Y. Tu, Kinjal Basu, +2 authors Shaunak Chatterjee
  • Published 2019
  • Computer Science, Mathematics
  • ArXiv
  • 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. However, the effect of any given treatment varies across experimental units, and choosing a single variant to ramp to the whole population can be quite suboptimal. In this work, we propose a method which… CONTINUE READING

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