AI RESEARCH
Beyond Objective-Based Improvement: Stationarity-Aware Expected Improvement for Bayesian Optimization
arXiv CS.LG
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ArXi:2601.21357v2 Announce Type: replace Bayesian Optimization (BO) is a principled framework for optimizing expensive black-box functions, with Expected Improvement (EI) among its most widely used acquisition functions. Despite its empirical success, EI is agnostic to first-order optimality conditions, relying solely on objective-value improvement. As a result, it can exhibit vanishing acquisition signals where the improvement criterion is uninformative, limiting its effectiveness in guiding search.