{"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/famesvd-fast-and-memory-efficient-singular","title":"Tutorial: Complexity analysis of Singular Value Decomposition and its variants","arxiv_id":"1906.12085","date":"2019-06-28","proceeding":null,"authors":["Xiaocan Li","Shuo Wang","Yinghao Cai"],"abstract":"We compared the regular Singular Value Decomposition (SVD), truncated SVD, Krylov method and Randomized PCA, in terms of time and space complexity. It is well-known that Krylov method and Randomized PCA only performs well when k << n, i.e. the number of eigenpair needed is far less than that of matrix size. We compared them for calculating all the eigenpairs. We also discussed the relationship between Principal Component Analysis and SVD.","url_abs":"https://arxiv.org/abs/1906.12085v3","url_pdf":"https://arxiv.org/pdf/1906.12085v3.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":"famesvd-fast-and-memory-efficient-singular","repo_url":"https://github.com/MxAR/FameSVD.jl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"famesvd-fast-and-memory-efficient-singular","repo_url":"https://github.com/UnofficialJuliaMirror/FameSVD.jl-9ba2d756-9ce3-11e9-1a71-0ffcb019784d","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"famesvd-fast-and-memory-efficient-singular","repo_url":"https://github.com/UnofficialJuliaMirrorSnapshots/FameSVD.jl-9ba2d756-9ce3-11e9-1a71-0ffcb019784d","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[],"methods":[{"method_slug":"pca","method_name":"PCA"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1906.12085","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}