Ax: A Platform for Adaptive Experimentation
We present Ax, an open-source platform for adaptive experimentation built on BoTorch. Off the shelf, Ax achieves state-of-the-art performance across a wide range of synthetic and …
Miles Olson
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1 min read
📄 One paper accepted to AutoML 2025
Our paper "Ax — A Platform for Adaptive Experimentation" was accepted to AutoML 2025 (ABCD Track).
💼 Joined Meta CAS Adaptive Experimentation
Started as a Research Scientist at Meta on the Adaptive Experimentation team within Central Applied Science (CAS), based in New York City.
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
📄 One paper accepted to NeurIPS 2022
Our paper "Batch Bayesian Optimisation via Density-ratio Estimation with Guarantees", led by Rafael Oliveira, was paper accepted to NeurIPS2022!
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1 min read
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, …