Reproducible feature selection in high-dimensional accelerated failure time models

We propose a new feature selection procedure with guaranteed FDR control for high-dimensional AFT models, which is among the first attempts of reproducible learning in survival analysis. The effectiveness of the proposed method is theoretically and numerically demonstrated.