3 papers
cs.LG2020
Cost-aware Bayesian Optimization
Eric Hans Lee, Valerio Perrone, Cedric Archambeau +1
Bayesian optimization (BO) is a class of global optimization algorithms, suitable for minimizing an expensive objective function in as few function evaluations as possible. While B…
cs.LG2020
Efficient Rollout Strategies for Bayesian Optimization
Eric Hans Lee, David Eriksson, Bolong Cheng +2
Bayesian optimization (BO) is a class of sample-efficient global optimization methods, where a probabilistic model conditioned on previous observations is used to determine future…
cs.LG2018
Scaling Gaussian Process Regression with Derivatives
David Eriksson, Kun Dong, Eric Hans Lee +2
Gaussian processes (GPs) with derivatives are useful in many applications, including Bayesian optimization, implicit surface reconstruction, and terrain reconstruction. Fitting a G…