{"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/less-is-more-nystrom-computational","title":"Less is More: Nyström Computational Regularization","arxiv_id":"1507.04717","date":"2015-07-16","proceeding":"NeurIPS 2015 12","authors":["Alessandro Rudi","Raffaello Camoriano","Lorenzo Rosasco"],"abstract":"We study Nystr\\\"om type subsampling approaches to large scale kernel methods,\nand prove learning bounds in the statistical learning setting, where random\nsampling and high probability estimates are considered. In particular, we prove\nthat these approaches can achieve optimal learning bounds, provided the\nsubsampling level is suitably chosen. These results suggest a simple\nincremental variant of Nystr\\\"om Kernel Regularized Least Squares, where the\nsubsampling level implements a form of computational regularization, in the\nsense that it controls at the same time regularization and computations.\nExtensive experimental analysis shows that the considered approach achieves\nstate of the art performances on benchmark large scale datasets.","url_abs":"http://arxiv.org/abs/1507.04717v6","url_pdf":"http://arxiv.org/pdf/1507.04717v6.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":"less-is-more-nystrom-computational","repo_url":"https://github.com/LCSL/NystromCoRe","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"BSD-3-Clause"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1507.04717","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}