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Efficiently Estimating Optimal Hyperparameter Scaling Laws through Power-Law Entropy Search
This work introduces Power-Law Entropy Search (PLES), a computational cost-aware acquisition function built on multi-fidelity Bayesian optimization that efficiently estimates optimal hyperparameter scaling laws through adaptive experimentation using less than one-tenth of the computational budget required by convention...