{"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-belief-propagation-for-approximate","title":"$α$ Belief Propagation for Approximate Inference","arxiv_id":"2006.15363","date":"2020-06-27","proceeding":null,"authors":["Dong Liu","Minh Thành Vu","Zuxing Li","Lars K. Rasmussen"],"abstract":"Belief propagation (BP) algorithm is a widely used message-passing method for inference in graphical models. BP on loop-free graphs converges in linear time. But for graphs with loops, BP's performance is uncertain, and the understanding of its solution is limited. To gain a better understanding of BP in general graphs, we derive an interpretable belief propagation algorithm that is motivated by minimization of a localized $\\alpha$-divergence. We term this algorithm as $\\alpha$ belief propagation ($\\alpha$-BP). It turns out that $\\alpha$-BP generalizes standard BP. In addition, this work studies the convergence properties of $\\alpha$-BP. We prove and offer the convergence conditions for $\\alpha$-BP. Experimental simulations on random graphs validate our theoretical results. The application of $\\alpha$-BP to practical problems is also demonstrated.","url_abs":"https://arxiv.org/abs/2006.15363v1","url_pdf":"https://arxiv.org/pdf/2006.15363v1.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":"a-belief-propagation-for-approximate","repo_url":"https://github.com/FirstHandScientist/AlphaBP","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}