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stat.ME2025
Efficient Log-Rank Updates for Random Survival Forests
Erik Sverdrup, James Yang, Michael LeBlanc
Random survival forests are widely used for estimating covariate-conditional survival functions under right-censoring. Their standard log-rank splitting criterion is typically reco…
stat.ML2025
Statistical Learning for Heterogeneous Treatment Effects: Pretraining, Prognosis, and Prediction
Maximilian Schuessler, Erik Sverdrup, Robert Tibshirani
Robust estimation of heterogeneous treatment effects is a fundamental challenge for optimal decision-making in domains ranging from personalized medicine to educational policy. In…