363 citations · 1.1k across the 50 of their papers we have counts for
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Bayesian Optimization of Function Networks
Raul Astudillo, Peter I. Frazier
We consider Bayesian optimization of the output of a network of functions, where each function takes as input the output of its parent nodes, and where the network takes significan…
Two-step Lookahead Bayesian Optimization with Inequality Constraints
Yunxiang Zhang, Xiangyu Zhang, Peter I. Frazier
Recent advances in computationally efficient non-myopic Bayesian optimization (BO) improve query efficiency over traditional myopic methods like expected improvement while only mod…
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs
Raul Astudillo, Daniel R. Jiang, Maximilian Balandat +2
Bayesian optimization (BO) is a sample-efficient approach to optimizing costly-to-evaluate black-box functions. Most BO methods ignore how evaluation costs may vary over the optimi…
Correlation Improves Group Testing: Modeling Concentration-Dependent Test Errors
Jiayue Wan, Yujia Zhang, Peter I. Frazier
Population-wide screening is a powerful tool for controlling infectious diseases. Group testing enables such screening despite limited resources. Viral concentration of pooled samp…
Restless Bandits with Many Arms: Beating the Central Limit Theorem
Xiangyu Zhang, Peter I. Frazier
We consider finite-horizon restless bandits with multiple pulls per period, which play an important role in recommender systems, active learning, revenue management, and many other…