56 citations · 64 across the 3 of their papers we have counts for
4 papers
Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning
Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier +1
Bayesian optimization is popular for optimizing time-consuming black-box objectives. Nonetheless, for hyperparameter tuning in deep neural networks, the time required to evaluate t…
Bayesian Optimization with Expensive Integrands
Saul Toscano-Palmerin, Peter I. Frazier
We propose a Bayesian optimization algorithm for objective functions that are sums or integrals of expensive-to-evaluate functions, allowing noisy evaluations. These objective func…
Stratified Bayesian Optimization
Saul Toscano-Palmerin, Peter I. Frazier
We consider derivative-free black-box global optimization of expensive noisy functions, when most of the randomness in the objective is produced by a few influential scalar random…
Asymptotic Validity of the Bayes-Inspired Indifference Zone Procedure: The Non-Normal Known Variance Case
Saul Toscano-Palmerin, Peter I. Frazier
We consider the indifference-zone (IZ) formulation of the ranking and selection problem in which the goal is to choose an alternative with the largest mean with guaranteed probabil…