English

Limbo: A Fast and Flexible Library for Bayesian Optimization

Machine Learning 2016-11-23 v1 Artificial Intelligence Robotics Machine Learning

Abstract

Limbo is an open-source C++11 library for Bayesian optimization which is designed to be both highly flexible and very fast. It can be used to optimize functions for which the gradient is unknown, evaluations are expensive, and runtime cost matters (e.g., on embedded systems or robots). Benchmarks on standard functions show that Limbo is about 2 times faster than BayesOpt (another C++ library) for a similar accuracy.

Keywords

Cite

@article{arxiv.1611.07343,
  title  = {Limbo: A Fast and Flexible Library for Bayesian Optimization},
  author = {Antoine Cully and Konstantinos Chatzilygeroudis and Federico Allocati and Jean-Baptiste Mouret},
  journal= {arXiv preprint arXiv:1611.07343},
  year   = {2016}
}
R2 v1 2026-06-22T17:00:52.980Z