{"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/adanet-a-scalable-and-flexible-framework-for","title":"AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles","arxiv_id":"1905.00080","date":"2019-04-30","proceeding":null,"authors":["Charles Weill","Javier Gonzalvo","Vitaly Kuznetsov","Scott Yang","Scott Yak","Hanna Mazzawi","Eugen Hotaj","Ghassen Jerfel","Vladimir Macko","Ben Adlam","Mehryar Mohri","Corinna Cortes"],"abstract":"AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework for\nautomatically learning high-quality ensembles with minimal expert intervention.\nOur framework is inspired by the AdaNet algorithm (Cortes et al., 2017) which\nlearns the structure of a neural network as an ensemble of subnetworks. We\ndesigned it to: (1) integrate with the existing TensorFlow ecosystem, (2) offer\nsensible default search spaces to perform well on novel datasets, (3) present a\nflexible API to utilize expert information when available, and (4) efficiently\naccelerate training with distributed CPU, GPU, and TPU hardware. The code is\nopen-source and available at: https://github.com/tensorflow/adanet.","url_abs":"http://arxiv.org/abs/1905.00080v1","url_pdf":"http://arxiv.org/pdf/1905.00080v1.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":"adanet-a-scalable-and-flexible-framework-for","repo_url":"https://github.com/tensorflow/adanet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":null,"task_name":"CPU"},{"task_slug":null,"task_name":"GPU"},{"task_slug":"architecture-search","task_name":"Neural Architecture Search"}],"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}