Conformalized Super Learner

arXiv:2604.22391 · stat.ML, cs.LG, stat.CO, stat.ME · Submitted 2026-04-24 · Read on arXiv

stat.ML, cs.LG, stat.CO, stat.ME

Submitted: 2026-04-24

Updated: 2026-09-08

Comments: R codes and data can be found at: https://github.com/ZWU-001/CSL

Code: https://github.com/ZWU-001/CSL

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Super Learner — 51× in this paper
• Conformal Prediction — 35× in this paper · explained in 5 episodes
• Conformalized Super Learner — 34× in this paper
• Aggregation — 24× in this paper · explained in 1 episode
• Calibration — 15× in this paper · explained in 7 episodes
• Exchangeability — 13× in this paper · explained in 2 episodes
• Heteroscedasticity — 11× in this paper · explained in 2 episodes
• Empirical Coverage — 10× in this paper · explained in 2 episodes
• Sparsity — 6× in this paper · explained in 4 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Theoretical Guarantees — 3× in this paper · explained in 2 episodes
• Centers for Disease Control and Prevention — 2× in this paper
• Core — 2× in this paper · explained in 2 episodes
• Covariate Shift — 2× in this paper · explained in 2 episodes
• National Center for Health Statistics — 2× in this paper
• National Health and Nutrition Examination Survey — 2× in this paper
• Uncertainty Quantification — 2× in this paper · explained in 8 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptivity — 1× in this paper · explained in 1 episode
• Aggregation Function — 1× in this paper · explained in 1 episode
• Causal Inference — 1× in this paper · explained in 4 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Diagnostic Tools — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Ensemble Approach — 1× in this paper · explained in 3 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Least Absolute Shrinkage and Selection Operator — 1× in this paper
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Theoretical Foundations of Conformal Prediction
• Conformal online model aggregation
• Merging uncertainty sets via majority vote
• Conformal Prediction for Ensembles: Improving Efficiency via Score-Based Aggregation
• Conformalized Regression for Continuous Bounded Outcomes

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