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cs.LG2025
Enhancing Performance and Calibration in Quantile Hyperparameter Optimization
Riccardo Doyle
Bayesian hyperparameter optimization relies heavily on Gaussian Process (GP) surrogates, due to robust distributional posteriors and strong performance on limited training samples.…
cs.LG2022
ACHO: Adaptive Conformal Hyperparameter Optimization
Riccardo Doyle
Several novel frameworks for hyperparameter search have emerged in the last decade, but most rely on strict, often normal, distributional assumptions, limiting search model flexibi…