5.7k citations · 8.4k across the 42 of their papers we have counts for
4 papers · 1 filter
Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces
Kevin Swersky, David Duvenaud, Jasper Snoek +2
In practical Bayesian optimization, we must often search over structures with differing numbers of parameters. For instance, we may wish to search over neural network architectures…
Freeze-Thaw Bayesian Optimization
Kevin Swersky, Jasper Snoek, Ryan Prescott Adams
In this paper we develop a dynamic form of Bayesian optimization for machine learning models with the goal of rapidly finding good hyperparameter settings. Our method uses the part…
Bayesian Optimization with Unknown Constraints
Michael A. Gelbart, Jasper Snoek, Ryan P. Adams
Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective functions. Many real-world optimization problems of interes…
Input Warping for Bayesian Optimization of Non-stationary Functions
Jasper Snoek, Kevin Swersky, Richard S. Zemel +1
Bayesian optimization has proven to be a highly effective methodology for the global optimization of unknown, expensive and multimodal functions. The ability to accurately model di…