17 citations · 81 across the 20 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2016★ 13 cited
A sequential Monte Carlo approach to Thompson sampling for Bayesian optimization
Hildo Bijl, Thomas B. Schön, Jan-Willem van Wingerden +1
Bayesian optimization through Gaussian process regression is an effective method of optimizing an unknown function for which every measurement is expensive. It approximates the obj…
stat.ML2016
System Identification through Online Sparse Gaussian Process Regression with Input Noise
Hildo Bijl, Thomas B. Schön, Jan-Willem van Wingerden +1
There has been a growing interest in using non-parametric regression methods like Gaussian Process (GP) regression for system identification. GP regression does traditionally have…