Corpus ID: 88517585

A/B Testing in Dense Large-Scale Networks: Design and Inference

  title={A/B Testing in Dense Large-Scale Networks: Design and Inference},
  author={P. Nandy and Kinjal Basu and Shaunak Chatterjee and Y. Tu},
  journal={arXiv: Methodology},
  • P. Nandy, Kinjal Basu, +1 author Y. Tu
  • Published 2019
  • Mathematics
  • arXiv: Methodology
  • Design of experiments and estimation of treatment effects in large-scale networks, in the presence of strong interference, is a challenging and important problem. Most existing methods' performance deteriorates as the density of the network increases. In this paper, we present a novel strategy for accurately estimating the causal effects of a class of treatments in a dense large-scale network. First, we design an approximate randomized controlled experiment by solving an optimization problem to… CONTINUE READING

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