{"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/manifold-matching-using-shortest-path","title":"Manifold Matching using Shortest-Path Distance and Joint Neighborhood Selection","arxiv_id":"1412.4098","date":"2014-12-12","proceeding":null,"authors":["Cencheng Shen","Joshua T. Vogelstein","Carey E. Priebe"],"abstract":"Matching datasets of multiple modalities has become an important task in data\nanalysis. Existing methods often rely on the embedding and transformation of\neach single modality without utilizing any correspondence information, which\noften results in sub-optimal matching performance. In this paper, we propose a\nnonlinear manifold matching algorithm using shortest-path distance and joint\nneighborhood selection. Specifically, a joint nearest-neighbor graph is built\nfor all modalities. Then the shortest-path distance within each modality is\ncalculated from the joint neighborhood graph, followed by embedding into and\nmatching in a common low-dimensional Euclidean space. Compared to existing\nalgorithms, our approach exhibits superior performance for matching disparate\ndatasets of multiple modalities.","url_abs":"http://arxiv.org/abs/1412.4098v4","url_pdf":"http://arxiv.org/pdf/1412.4098v4.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":"manifold-matching-using-shortest-path","repo_url":"https://github.com/cshen6/MMSJ","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":"https://app.syntology.ai/?focus=1412.4098","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}