{"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/on-the-use-of-sparse-filtering-for-covariate","title":"On the Use of Sparse Filtering for Covariate Shift Adaptation","arxiv_id":"1607.06781","date":"2016-07-22","proceeding":null,"authors":["Fabio Massimo Zennaro","Ke Chen"],"abstract":"In this paper we formally analyse the use of sparse filtering algorithms to\nperform covariate shift adaptation. We provide a theoretical analysis of sparse\nfiltering by evaluating the conditions required to perform covariate shift\nadaptation. We prove that sparse filtering can perform adaptation only if the\nconditional distribution of the labels has a structure explained by a cosine\nmetric. To overcome this limitation, we propose a new algorithm, named periodic\nsparse filtering, and carry out the same theoretical analysis regarding\ncovariate shift adaptation. We show that periodic sparse filtering can perform\nadaptation under the looser and more realistic requirement that the conditional\ndistribution of the labels has a periodic structure, which may be satisfied,\nfor instance, by user-dependent data sets. We experimentally validate our\ntheoretical results on synthetic data. Moreover, we apply periodic sparse\nfiltering to real-world data sets to demonstrate that this simple and\ncomputationally efficient algorithm is able to achieve competitive\nperformances.","url_abs":"http://arxiv.org/abs/1607.06781v2","url_pdf":"http://arxiv.org/pdf/1607.06781v2.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":"on-the-use-of-sparse-filtering-for-covariate","repo_url":"https://github.com/FMZennaro/PSF","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"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}