Optimal Recovery Meets Bayesian Learning: Where Worst-Case Bounds Pay Off

arXiv:2609.29622 · stat.ML, cs.LG · Submitted 2026-08-29 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-08-29

Updated: 2026-08-29

Code: https://github.com/FrankHuang24/ALAS-BO

Terminology

• Benchmark — 56× in this paper · explained in 2 episodes
• Regret — 28× in this paper · explained in 3 episodes
• Calibration — 23× in this paper · explained in 7 episodes
• Ablation — 12× in this paper · explained in 1 episode
• Covariate Shift — 11× in this paper · explained in 2 episodes
• AUC — 10× in this paper · explained in 2 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Hilbert Space — 5× in this paper · explained in 2 episodes
• Acquisition Function — 3× in this paper · explained in 1 episode
• Bayesian Optimization — 3× in this paper · explained in 3 episodes
• Degeneracy — 3× in this paper · explained in 3 episodes
• Provenance — 3× in this paper · explained in 3 episodes
• Conformal Prediction — 2× in this paper · explained in 5 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Inverse Problem — 2× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Worst-case Optimal Recovery — 1× in this paper

Sources

• Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
• Nonlinear Optimal Recovery in Hilbert Spaces
• Optimal recovery of linear operators from information of random functions

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