A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning
E Brochu, VM Cora, N De Freitas - ar** for Bayesian optimization of non-stationary functions
Bayesian optimization has proven to be a highly effective methodology for the global
optimization of unknown, expensive and multimodal functions. The ability to accurately …
optimization of unknown, expensive and multimodal functions. The ability to accurately …
The variational Gaussian process
Variational inference is a powerful tool for approximate inference, and it has been recently
applied for representation learning with deep generative models. We develop the variational …
applied for representation learning with deep generative models. We develop the variational …