5 citations · 13 across the 3 of their papers we have counts for
3 papers · 1 filter
Many Objective Bayesian Optimization
Lucia Asencio Martín, Eduardo C. Garrido-Merchán
Some real problems require the evaluation of expensive and noisy objective functions. Moreover, the analytical expression of these objective functions may be unknown. These functio…
Multi-class Gaussian Process Classification with Noisy Inputs
Carlos Villacampa-Calvo, Bryan Zaldivar, Eduardo C. Garrido-Merchán +1
It is a common practice in the machine learning community to assume that the observed data are noise-free in the input attributes. Nevertheless, scenarios with input noise are comm…
Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes
Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Bayesian Optimization (BO) methods are useful for optimizing functions that are expen- sive to evaluate, lack an analytical expression and whose evaluations can be contaminated by…