September 18, 2021

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Differentially Private Variable Selection via the Knockoff Filter. (arXiv:2109.05402v1 [stat.ML])

The knockoff filter, recently developed by Barber and Candes, is an effective
procedure to perform variable selection with a controlled false discovery rate
(FDR). We propose a private version of the knockoff filter by incorporating
Gaussian and Laplace mechanisms, and show that variable selection with
controlled FDR can be achieved. Simulations demonstrate that our setting has
reasonable statistical power.