{"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/learning-to-generate-classifiers","title":"Learning to generate classifiers","arxiv_id":"1803.11373","date":"2018-03-30","proceeding":null,"authors":["Nicholas Guttenberg","Ryota Kanai"],"abstract":"We train a network to generate mappings between training sets and\nclassification policies (a 'classifier generator') by conditioning on the\nentire training set via an attentional mechanism. The network is directly\noptimized for test set performance on an training set of related tasks, which\nis then transferred to unseen 'test' tasks. We use this to optimize for\nperformance in the low-data and unsupervised learning regimes, and obtain\nsignificantly better performance in the 10-50 datapoint regime than support\nvector classifiers, random forests, XGBoost, and k-nearest neighbors on a range\nof small datasets.","url_abs":"http://arxiv.org/abs/1803.11373v1","url_pdf":"http://arxiv.org/pdf/1803.11373v1.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":"learning-to-generate-classifiers","repo_url":"https://github.com/arayabrain/ClassifierGenerators","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}