{"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/primal-dual-block-generalized-frank-wolfe","title":"Primal-Dual Block Generalized Frank-Wolfe","arxiv_id":null,"date":"2019-12-01","proceeding":"NeurIPS 2019 12","authors":["Qi Lei","Jiacheng Zhuo","Constantine Caramanis","Inderjit S. Dhillon","Alexandros G. Dimakis"],"abstract":"We propose a generalized variant of Frank-Wolfe algorithm for solving a class of sparse/low-rank optimization problems. Our formulation includes Elastic Net, regularized SVMs and phase retrieval as special cases. The proposed Primal-Dual Block Generalized Frank-Wolfe algorithm reduces the per-iteration cost while maintaining linear convergence rate.\nThe per iteration cost of our method depends on the structural complexity of the solution (i.e. sparsity/low-rank) instead of the ambient dimension.\nWe empirically show that our algorithm outperforms the state-of-the-art methods on (multi-class) classification tasks.","url_abs":"http://papers.nips.cc/paper/9538-primal-dual-block-generalized-frank-wolfe","url_pdf":"http://papers.nips.cc/paper/9538-primal-dual-block-generalized-frank-wolfe.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":"primal-dual-block-generalized-frank-wolfe","repo_url":"https://github.com/CarlsonZhuo/primal_dual_frank_wolfe","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"multi-class-classification","task_name":"Multi-class Classification"},{"task_slug":"retrieval","task_name":"Retrieval"}],"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}