Doubly Bayesian Optimization [article]

Alexander Lavin
2019 arXiv   pre-print
Probabilistic programming systems enable users to encode model structure and naturally reason about uncertainties, which can be leveraged towards improved Bayesian optimization (BO) methods. Here we present a probabilistic program embedding of BO that is capable of addressing main issues such as problematic domains (noisy, non-smooth, high-dimensional) and the neglected inner-optimization. Not only can we utilize programmable structure to incorporate domain knowledge to aid optimization, but
more » ... ling with uncertainties and implementing advanced BO techniques become trivial, crucial for use in practice (particularly for non-experts). We demonstrate the efficacy of the approach on optimization benchmarks and a real-world drug development scenario.
arXiv:1812.04562v4 fatcat:jaatj5drsbe5njwpl3fhs7tjeq