AI RESEARCH
Practical Efficient Global Optimization is No-regret
arXiv CS.LG
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ArXi:2603.25311v1 Announce Type: cross Efficient global optimization (EGO) is one of the most widely used noise-free Bayesian optimization algorithms. It comprises the Gaussian process (GP) surrogate model and expected improvement (EI) acquisition function. In practice, when EGO is applied, a scalar matrix of a small positive value (also called a nugget or jitter) is usually added to the covariance matrix of the deterministic GP to improve numerical stability. We refer to this EGO with a positive nugget as the practical.