Long Talk: BORE — Bayesian Optimization by Density-Ratio Estimation
The 38th International Conference on Machine Learning (ICML 2021), virtual.
Invited Talk: BORE — Bayesian Optimization by Density-Ratio Estimation
ELLIS AutoML Seminars (virtual).
BORE: Bayesian Optimization by Density-Ratio Estimation
We reformulate the computation of the acquisition function in Bayesian optimization (BO) as a probabilistic classification problem, providing advantages in scalability, …
📄 One paper accepted to ICML 2021
Our paper "BORE — Bayesian Optimization by Density-Ratio Estimation" was accepted to ICML 2021 as a Long Talk (top 3% of submissions).
An Illustrated Guide to the Knowledge Gradient Acquisition Function
We give a short illustrated reference guide to the Knowledge Gradient acquisition function with an implementation from scratch in TensorFlow Probability.
Contributed Talk: BORE — Bayesian Optimization by Density-Ratio Estimation
NeurIPS 2020 4th Workshop on Meta-Learning (virtual).
Bayesian Optimization by Density Ratio Estimation
Model-based Asynchronous Hyperparameter and Neural Architecture Search
We introduce a model-based method for asynchronous multi-fidelity hyperparameter and neural architecture search that combines the strengths of asynchronous Hyperband and Gaussian …
Aaron Klein