[{"article_processing_charge":"No","date_published":"2006-03-01T00:00:00Z","day":"01","publication_status":"published","page":"149-171","intvolume":"        13","issue":"2-3","year":"2006","citation":{"mla":"Bronstein, M. M., et al. “Multigrid Multidimensional Scaling.” <i>Numerical Linear Algebra with Applications</i>, vol. 13, no. 2–3, Wiley, 2006, pp. 149–71, doi:<a href=\"https://doi.org/10.1002/nla.475\">10.1002/nla.475</a>.","apa":"Bronstein, M. M., Bronstein, A. M., Kimmel, R., &#38; Yavneh, I. (2006). Multigrid multidimensional scaling. <i>Numerical Linear Algebra with Applications</i>. Wiley. <a href=\"https://doi.org/10.1002/nla.475\">https://doi.org/10.1002/nla.475</a>","short":"M.M. Bronstein, A.M. Bronstein, R. Kimmel, I. Yavneh, Numerical Linear Algebra with Applications 13 (2006) 149–171.","ama":"Bronstein MM, Bronstein AM, Kimmel R, Yavneh I. Multigrid multidimensional scaling. <i>Numerical Linear Algebra with Applications</i>. 2006;13(2-3):149-171. doi:<a href=\"https://doi.org/10.1002/nla.475\">10.1002/nla.475</a>","ista":"Bronstein MM, Bronstein AM, Kimmel R, Yavneh I. 2006. Multigrid multidimensional scaling. Numerical Linear Algebra with Applications. 13(2–3), 149–171.","chicago":"Bronstein, M. M., Alex M. Bronstein, R. Kimmel, and I. Yavneh. “Multigrid Multidimensional Scaling.” <i>Numerical Linear Algebra with Applications</i>. Wiley, 2006. <a href=\"https://doi.org/10.1002/nla.475\">https://doi.org/10.1002/nla.475</a>.","ieee":"M. M. Bronstein, A. M. Bronstein, R. Kimmel, and I. Yavneh, “Multigrid multidimensional scaling,” <i>Numerical Linear Algebra with Applications</i>, vol. 13, no. 2–3. Wiley, pp. 149–171, 2006."},"publisher":"Wiley","date_updated":"2024-11-12T08:45:09Z","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Numerical Linear Algebra with Applications","oa_version":"None","scopus_import":"1","author":[{"full_name":"Bronstein, M. M.","first_name":"M. M.","last_name":"Bronstein"},{"last_name":"Bronstein","first_name":"Alexander","full_name":"Bronstein, Alexander","orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6"},{"full_name":"Kimmel, R.","first_name":"R.","last_name":"Kimmel"},{"last_name":"Yavneh","first_name":"I.","full_name":"Yavneh, I."}],"extern":"1","article_type":"original","date_created":"2024-10-15T11:12:06Z","month":"03","abstract":[{"text":"Multidimensional scaling (MDS) is a generic name for a family of algorithms that construct a configuration of points in a target metric space from information about inter-point distances measured in some other metric space. Large-scale MDS problems often occur in data analysis, representation and visualization. Solving such problems efficiently is of key importance in many applications.\r\nIn this paper we present a multigrid framework for MDS problems. We demonstrate the performance of our algorithm on dimensionality reduction and isometric embedding problems, two classical problems requiring efficient large-scale MDS. Simulation results show that the proposed approach significantly outperforms conventional MDS algorithms.","lang":"eng"}],"quality_controlled":"1","status":"public","_id":"18318","title":"Multigrid multidimensional scaling","publication_identifier":{"eissn":["1099-1506"],"issn":["1070-5325"]},"volume":13,"doi":"10.1002/nla.475","type":"journal_article"}]