Corpus ID: 211532640

PAPRIKA: Private Online False Discovery Rate Control

@article{Zhang2021PAPRIKAPO,
  title={PAPRIKA: Private Online False Discovery Rate Control},
  author={Wanrong Zhang and Gautam Kamath and Rachel Cummings},
  journal={ArXiv},
  year={2021},
  volume={abs/2002.12321}
}
In hypothesis testing, a false discovery occurs when a hypothesis is incorrectly rejected due to noise in the sample. When adaptively testing multiple hypotheses, the probability of a false discovery increases as more tests are performed. Thus the problem of False Discovery Rate (FDR) control is to find a procedure for testing multiple hypotheses that accounts for this effect in determining the set of hypotheses to reject. The goal is to minimize the number (or fraction) of false discoveries… Expand

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