An Optimality Framework for Supersaturated Screening with the Lasso

Music City Center 

Supersaturated Screening Designs (SSDs) are used for factor screening when there are more experimental factors than there are experimental runs. In this case, penalized estimation is commonly applied to analyze these experiments. This work proposes a framework for optimal SSDs in the context of the exact probability of lasso support recovery.