{"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/accelerated-gradient-boosting","title":"Accelerated Gradient Boosting","arxiv_id":"1803.02042","date":"2018-03-06","proceeding":null,"authors":["Gérard Biau","Benoît Cadre","Laurent Rouvìère"],"abstract":"Gradient tree boosting is a prediction algorithm that sequentially produces a\nmodel in the form of linear combinations of decision trees, by solving an\ninfinite-dimensional optimization problem. We combine gradient boosting and\nNesterov's accelerated descent to design a new algorithm, which we call AGB\n(for Accelerated Gradient Boosting). Substantial numerical evidence is provided\non both synthetic and real-life data sets to assess the excellent performance\nof the method in a large variety of prediction problems. It is empirically\nshown that AGB is much less sensitive to the shrinkage parameter and outputs\npredictors that are considerably more sparse in the number of trees, while\nretaining the exceptional performance of gradient boosting.","url_abs":"http://arxiv.org/abs/1803.02042v1","url_pdf":"http://arxiv.org/pdf/1803.02042v1.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":"accelerated-gradient-boosting","repo_url":"https://github.com/lrouviere/AGB","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.02042","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}