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Enhanced Gaussian Process Surrogates for Optimization and Sampling by Pure Exploration – Hwanwoo Kim
Enhanced Gaussian Process Surrogates for Optimization and Sampling by Pure Exploration – Hwanwoo Kim
Abstract: In this talk, we propose novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. …