{"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/online-asynchronous-distributed-regression","title":"Online Asynchronous Distributed Regression","arxiv_id":"1407.4373","date":"2014-07-16","proceeding":null,"authors":["Gérard Biau","Ryad Zenine"],"abstract":"Distributed computing offers a high degree of flexibility to accommodate\nmodern learning constraints and the ever increasing size of datasets involved\nin massive data issues. Drawing inspiration from the theory of distributed\ncomputation models developed in the context of gradient-type optimization\nalgorithms, we present a consensus-based asynchronous distributed approach for\nnonparametric online regression and analyze some of its asymptotic properties.\nSubstantial numerical evidence involving up to 28 parallel processors is\nprovided on synthetic datasets to assess the excellent performance of our\nmethod, both in terms of computation time and prediction accuracy.","url_abs":"http://arxiv.org/abs/1407.4373v1","url_pdf":"http://arxiv.org/pdf/1407.4373v1.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":"online-asynchronous-distributed-regression","repo_url":"https://github.com/ryadzenine/dolphin","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"distributed-computing","task_name":"Distributed Computing"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}