5.2k citations · 7.9k across the 34 of their papers we have counts for
4 papers · 1 filter
Learning unbiased features
Yujia Li, Kevin Swersky, Richard Zemel
A key element in transfer learning is representation learning; if representations can be developed that expose the relevant factors underlying the data, then new tasks and domains…
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…
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…