On the Selection Stability of Stability Selection and Its Applications
This work extends stability selection by creating 'stable stability selection' to assess overall result robustness instead of individual variables. It introduces a new estimator and identifies a Pareto optimal regularization value that balances high stability with low prediction loss, providing a better way to tune Lasso models.