{"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/large-margin-classification-in-hyperbolic","title":"Large-Margin Classification in Hyperbolic Space","arxiv_id":"1806.00437","date":"2018-06-01","proceeding":null,"authors":["Hyunghoon Cho","Benjamin DeMeo","Jian Peng","Bonnie Berger"],"abstract":"Representing data in hyperbolic space can effectively capture latent\nhierarchical relationships. With the goal of enabling accurate classification\nof points in hyperbolic space while respecting their hyperbolic geometry, we\nintroduce hyperbolic SVM, a hyperbolic formulation of support vector machine\nclassifiers, and elucidate through new theoretical work its connection to the\nEuclidean counterpart. We demonstrate the performance improvement of hyperbolic\nSVM for multi-class prediction tasks on real-world complex networks as well as\nsimulated datasets. Our work allows analytic pipelines that take the inherent\nhyperbolic geometry of the data into account in an end-to-end fashion without\nresorting to ill-fitting tools developed for Euclidean space.","url_abs":"http://arxiv.org/abs/1806.00437v1","url_pdf":"http://arxiv.org/pdf/1806.00437v1.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":"large-margin-classification-in-hyperbolic","repo_url":"https://github.com/hhcho/hyplinear","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"large-margin-classification-in-hyperbolic","repo_url":"https://github.com/plumdeq/hsvm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[{"method_slug":"svm","method_name":"SVM"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.00437","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}