398 citations · 530 across the 3 of their papers we have counts for
3 papers
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions
José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani
We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that ma…
An Entropy Search Portfolio for Bayesian Optimization
Bobak Shahriari, Ziyu Wang, Matthew W. Hoffman +2
Bayesian optimization is a sample-efficient method for black-box global optimization. How- ever, the performance of a Bayesian optimization method very much depends on its explorat…
Portfolio Allocation for Bayesian Optimization
Eric Brochu, Matthew W. Hoffman, Nando de Freitas
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known a…