BORE

Jul 1, 2021 · 1 min read
projects

BORE is the reference implementation of Bayesian Optimization by Density-Ratio Estimation (Tiao et al., ICML 2021). It recasts the acquisition function in Bayesian optimization as a probabilistic classification problem via density-ratio estimation, sidestepping the analytical-tractability constraints of conventional surrogate-based methods.

Developed with Aaron Klein.

Bayesian Optimization Density Ratio Estimation Hyperparameter Optimization Open Source AutoML
Louis Tiao
Authors
Louis Tiao
Research Scientist
My name is Louis Tiao, and I graduated from one of Australia’s top engineering schools with really good grades. Now, I’m using my knowledge to help up-and-coming tech companies make it in this competitive world.