{"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/a-unified-non-negative-matrix-factorization","title":"A Unified Non-Negative Matrix Factorization Framework for Semi-Supervised Learning on Graphs","arxiv_id":null,"date":"2020-04-01","proceeding":"Proceedings of the 2020 SIAM International Conference on Data Mining 2020 4","authors":["Anasua Mitra","Priyesh Vijayan","Srinivasan Parthasarathy","Balaraman Ravindran"],"abstract":"We propose a Semi-Supervised Learning (SSL) methodology that explicitly encodes different necessary priors to learn\r\nefficient representations for nodes in a network. The key to our framework is a semi-supervised cluster invariance\r\nconstraint that explicitly groups nodes of similar labels together. We show that explicitly encoding this constraint\r\nallows one to learn meaningful node representations from both qualitative (visual) and quantitative standpoints. Specifically,\r\nour methodology realizes improved node classification and visually-enhanced clusterability of nodes on a wide range of\r\ndatasets over competitive baselines.","url_abs":"https://epubs.siam.org/doi/10.1137/1.9781611976236.55","url_pdf":"https://epubs.siam.org/doi/pdf/10.1137/1.9781611976236.55","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":"a-unified-non-negative-matrix-factorization","repo_url":"https://github.com/sonaidgr8/USS_NMF","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"node-classification","task_name":"Node Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}