{"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/predictive-entropy-search-for-efficient","title":"Predictive Entropy Search for Efficient Global Optimization of Black-box Functions","arxiv_id":"1406.2541","date":"2014-06-10","proceeding":"NeurIPS 2014 12","authors":["José Miguel Hernández-Lobato","Matthew W. Hoffman","Zoubin Ghahramani"],"abstract":"We propose a novel information-theoretic approach for Bayesian optimization\ncalled Predictive Entropy Search (PES). At each iteration, PES selects the next\nevaluation point that maximizes the expected information gained with respect to\nthe global maximum. PES codifies this intractable acquisition function in terms\nof the expected reduction in the differential entropy of the predictive\ndistribution. This reformulation allows PES to obtain approximations that are\nboth more accurate and efficient than other alternatives such as Entropy Search\n(ES). Furthermore, PES can easily perform a fully Bayesian treatment of the\nmodel hyperparameters while ES cannot. We evaluate PES in both synthetic and\nreal-world applications, including optimization problems in machine learning,\nfinance, biotechnology, and robotics. We show that the increased accuracy of\nPES leads to significant gains in optimization performance.","url_abs":"http://arxiv.org/abs/1406.2541v1","url_pdf":"http://arxiv.org/pdf/1406.2541v1.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":"predictive-entropy-search-for-efficient","repo_url":"https://github.com/chongkewu/PESC-HPC","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"bayesian-optimization","task_name":"Bayesian Optimization"},{"task_slug":"global-optimization","task_name":"global-optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1406.2541","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}