most citedA Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

2.1k citations · 2.3k across the 3 of their papers we have counts for

collaborators

3 papers

stat.ML2017★ 11 cited

Optimal Sub-sampling with Influence Functions

Daniel Ting, Eric Brochu

Sub-sampling is a common and often effective method to deal with the computational challenges of large datasets. However, for most statistical models, there is no well-motivated ap…

cs.LG2010★ 2.1k cited

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

Eric Brochu, Vlad M. Cora, Nando de Freitas

We present a tutorial on Bayesian optimization, a method of finding the maximum of expensive cost functions. Bayesian optimization employs the Bayesian technique of setting a prior…

cs.LG2010★ 91 cited

Portfolio Allocation for Bayesian Optimization

Eric Brochu, Matthew W. Hoffman, Nando de Freitas

Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known a…