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Conformal Prediction

Conformal Prediction

ConfOpt: Conformalized Quantile Regression Sampler

Abstract ConfOptSampler provides flexible and robust hyperparameter optimization via calibrated quantile regression surrogates. It supports the following acquisition functions: Thompson Sampling Optimistic Bayesian Sampling Expected Improvement It is robust to heteroskedastic, skewed, non-normal and highly categorical environments where traditional GPs might fail. Its single-fidelity performance in popular HPO benchmarks puts it consistently ahead of TPE and SMAC and contextually ahead of GPs (when hyperparameters are categorical): API ConfOptSampler class takes the following parameters: