{"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/applied-federated-learning-improving-google","title":"Applied Federated Learning: Improving Google Keyboard Query Suggestions","arxiv_id":"1812.02903","date":"2018-12-07","proceeding":null,"authors":["Timothy Yang","Galen Andrew","Hubert Eichner","Haicheng Sun","Wei Li","Nicholas Kong","Daniel Ramage","Françoise Beaufays"],"abstract":"Federated learning is a distributed form of machine learning where both the\ntraining data and model training are decentralized. In this paper, we use\nfederated learning in a commercial, global-scale setting to train, evaluate and\ndeploy a model to improve virtual keyboard search suggestion quality without\ndirect access to the underlying user data. We describe our observations in\nfederated training, compare metrics to live deployments, and present resulting\nquality increases. In whole, we demonstrate how federated learning can be\napplied end-to-end to both improve user experiences and enhance user privacy.","url_abs":"http://arxiv.org/abs/1812.02903v1","url_pdf":"http://arxiv.org/pdf/1812.02903v1.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":"applied-federated-learning-improving-google","repo_url":"https://github.com/jaemin-shin/fedbalancer","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"federated-learning","task_name":"Federated Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1812.02903","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}