Search Results for author: Eric Hans Lee

Found 4 papers, 3 papers with code

A Nonmyopic Approach to Cost-Constrained Bayesian Optimization

1 code implementation10 Jun 2021 Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias Seeger

Bayesian optimization (BO) is a popular method for optimizing expensive-to-evaluate black-box functions.

Hyperparameter Optimization

Cost-aware Bayesian Optimization

no code implementations22 Mar 2020 Eric Hans Lee, Valerio Perrone, Cedric Archambeau, Matthias Seeger

Bayesian optimization (BO) is a class of global optimization algorithms, suitable for minimizing an expensive objective function in as few function evaluations as possible.

Efficient Rollout Strategies for Bayesian Optimization

1 code implementation24 Feb 2020 Eric Hans Lee, David Eriksson, Bolong Cheng, Michael McCourt, David Bindel

Non-myopic acquisition functions consider the impact of the next $h$ function evaluations and are typically computed through rollout, in which $h$ steps of BO are simulated.

Scaling Gaussian Process Regression with Derivatives

1 code implementation NeurIPS 2018 David Eriksson, Kun Dong, Eric Hans Lee, David Bindel, Andrew Gordon Wilson

Gaussian processes (GPs) with derivatives are useful in many applications, including Bayesian optimization, implicit surface reconstruction, and terrain reconstruction.

Dimensionality Reduction Gaussian Processes +1

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