Efficient Cholesky decomposition of low-rank updates
We give a short and practical guide to efficiently computing the Cholesky decomposition of matrices perturbed by low-rank updates.
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.
Batch Bayesian Optimisation via Density-ratio Estimation with Guarantees
We extend BORE to the batch setting and establish theoretical convergence guarantees for parallel Bayesian optimization.
rafael-oliveira
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).
A Primer on Pólya-gamma Random Variables - Part II: Bayesian Logistic Regression
We use one weird trick — Pólya-Gamma augmentation — to make exact inference in Bayesian logistic regression tractable.
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).