{"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/online-structure-learning-for-sum-product","title":"Online Structure Learning for Sum-Product Networks with Gaussian Leaves","arxiv_id":"1701.05265","date":"2017-01-19","proceeding":null,"authors":["Wilson Hsu","Agastya Kalra","Pascal Poupart"],"abstract":"Sum-product networks have recently emerged as an attractive representation\ndue to their dual view as a special type of deep neural network with clear\nsemantics and a special type of probabilistic graphical model for which\ninference is always tractable. Those properties follow from some conditions\n(i.e., completeness and decomposability) that must be respected by the\nstructure of the network. As a result, it is not easy to specify a valid\nsum-product network by hand and therefore structure learning techniques are\ntypically used in practice. This paper describes the first online structure\nlearning technique for continuous SPNs with Gaussian leaves. We also introduce\nan accompanying new parameter learning technique.","url_abs":"http://arxiv.org/abs/1701.05265v1","url_pdf":"http://arxiv.org/pdf/1701.05265v1.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":"online-structure-learning-for-sum-product","repo_url":"https://github.com/whsu/spn","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":null,"task_name":"valid"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}