{"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/multi-view-kernel-completion","title":"Multi-view Kernel Completion","arxiv_id":"1602.02518","date":"2016-02-08","proceeding":null,"authors":["Sahely Bhadra","Samuel Kaski","Juho Rousu"],"abstract":"In this paper, we introduce the first method that (1) can complete kernel\nmatrices with completely missing rows and columns as opposed to individual\nmissing kernel values, (2) does not require any of the kernels to be complete a\npriori, and (3) can tackle non-linear kernels. These aspects are necessary in\npractical applications such as integrating legacy data sets, learning under\nsensor failures and learning when measurements are costly for some of the\nviews. The proposed approach predicts missing rows by modelling both\nwithin-view and between-view relationships among kernel values. We show, both\non simulated data and real world data, that the proposed method outperforms\nexisting techniques in the restricted settings where they are available, and\nextends applicability to new settings.","url_abs":"http://arxiv.org/abs/1602.02518v1","url_pdf":"http://arxiv.org/pdf/1602.02518v1.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":"multi-view-kernel-completion","repo_url":"https://github.com/aalto-ics-kepaco/MKC","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"multi-view-kernel-completion","repo_url":"https://github.com/aalto-ics-kepaco/MKC_software","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}