{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/limbo-a-fast-and-flexible-library-for","title":"Limbo: A Fast and Flexible Library for Bayesian Optimization","arxiv_id":"1611.07343","date":"2016-11-22","proceeding":null,"authors":["Antoine Cully","Konstantinos Chatzilygeroudis","Federico Allocati","Jean-Baptiste Mouret"],"abstract":"Limbo is an open-source C++11 library for Bayesian optimization which is\ndesigned to be both highly flexible and very fast. It can be used to optimize\nfunctions for which the gradient is unknown, evaluations are expensive, and\nruntime cost matters (e.g., on embedded systems or robots). Benchmarks on\nstandard functions show that Limbo is about 2 times faster than BayesOpt\n(another C++ library) for a similar accuracy.","url_abs":"http://arxiv.org/abs/1611.07343v1","url_pdf":"http://arxiv.org/pdf/1611.07343v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"limbo-a-fast-and-flexible-library-for","repo_url":"https://github.com/resibots/limbo","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"bayesian-optimization","task_name":"Bayesian Optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}