From Random Search to Bandit Learning in Metric Measure Spaces

no code implementations • 19 May 2023 • Chuying Han, Yasong Feng, Tianyu Wang

We show that, when the environment is noise-free, the output of random search converges to the optimal value in probability at rate $ \widetilde{\mathcal{O}} \left( \left( \frac{1}{T} \right)^{ \frac{1}{d_s} } \right) $, where $ d_s \ge 0 $ is the scattering dimension of the underlying function.

Hyperparameter Optimization