{"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/fast-and-robust-archetypal-analysis-for","title":"Fast and Robust Archetypal Analysis for Representation Learning","arxiv_id":"1405.6472","date":"2014-05-26","proceeding":"CVPR 2014 6","authors":["Yuansi Chen","Julien Mairal","Zaid Harchaoui"],"abstract":"We revisit a pioneer unsupervised learning technique called archetypal\nanalysis, which is related to successful data analysis methods such as sparse\ncoding and non-negative matrix factorization. Since it was proposed, archetypal\nanalysis did not gain a lot of popularity even though it produces more\ninterpretable models than other alternatives. Because no efficient\nimplementation has ever been made publicly available, its application to\nimportant scientific problems may have been severely limited. Our goal is to\nbring back into favour archetypal analysis. We propose a fast optimization\nscheme using an active-set strategy, and provide an efficient open-source\nimplementation interfaced with Matlab, R, and Python. Then, we demonstrate the\nusefulness of archetypal analysis for computer vision tasks, such as codebook\nlearning, signal classification, and large image collection visualization.","url_abs":"http://arxiv.org/abs/1405.6472v1","url_pdf":"http://arxiv.org/pdf/1405.6472v1.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":"fast-and-robust-archetypal-analysis-for","repo_url":"https://github.com/vitkl/ParetoTI","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"representation-learning","task_name":"Representation Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1405.6472","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}