Controlling the False Discovery Rate via Competition: is the +1 needed?

Barber and Candès (2015) control of the FDR in feature selection relies on estimating the FDR by the number of knockoff wins +1 divided by the number of original wins. We study the necessity of the +1 in general settings.

Adversarial Robustness in Machine Learning Explainable Artificial Intelligence (XAI)Imbalanced Data Classification Techniques

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