143 citations · 179 across the 11 of their papers we have counts for
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stat.ML2019
Bayesian Optimization Allowing for Common Random Numbers
Michael Pearce, Matthias Poloczek, Juergen Branke
Bayesian optimization is a powerful tool for expensive stochastic black-box optimization problems such as simulation-based optimization or machine learning hyperparameter tuning. M…
cs.LG2019★ 143 cited
Scalable Global Optimization via Local Bayesian Optimization
David Eriksson, Michael Pearce, Jacob R Gardner +2
Bayesian optimization has recently emerged as a popular method for the sample-efficient optimization of expensive black-box functions. However, the application to high-dimensional…