2019

ProBO: Versatile Bayesian Optimization Using Any Probabilistic Programming Language

Neiswanger, Willie, Kandasamy, Kirthevasan, Poczos, Barnabas et al.

Understand

Optimizing an expensive-to-query function is a common task in science and engineering, where it is beneficial to keep the number of queries to a minimum.

  • A popular strategy is Bayesian optimization (BO), which leverages probabilistic models for this task.
  • Most BO today uses Gaussian processes (GPs), or a few other surrogate models.
  • However, there is a broad set of Bayesian modeling techniques that could be used to capture complex systems and reduce the number of queries in BO.

Reading the bibliography…