{"id":323165,"date":"2016-11-16T16:13:20","date_gmt":"2016-11-17T00:13:20","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=323165"},"modified":"2018-10-16T20:24:43","modified_gmt":"2018-10-17T03:24:43","slug":"reformulating-inference-problems-selective-conditioning","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/reformulating-inference-problems-selective-conditioning\/","title":{"rendered":"Reformulating Inference Problems Through Selective Conditioning"},"content":{"rendered":"<p><span lang=\"EN\">We describe how we selectively reformulate portions of a belief network that pose difficulties for solution with a stochastic-simulation algorithm. With employ the selective conditioning approach to target specific nodes in a belief network for decomposition, based on the contribution the nodes make to the tractability of stochastic simulation. We review previous work on BNRAS algorithms- randomized approximation algorithms for probabilistic inference. We show how selective conditioning can be employed to reformulate a single BNRAS problem into multiple tractable BNRAS simulation problems. We discuss how we can use another simulation algorithm-logic sampling-to solve a component of the inference problem that provides a means for knitting the solutions of individual subproblems into a final result. Finally, we analyze tradeoffs among the computational subtasks associated with the selective conditioning approach to reformulation.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We describe how we selectively reformulate portions of a belief network that pose difficulties for solution with a stochastic-simulation algorithm. With employ the selective conditioning approach to target specific nodes in a belief network for decomposition, based on the contribution the nodes make to the tractability of stochastic simulation. We review previous work on BNRAS [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence","msr_editors":"","msr_how_published":"","msr_isbn":"1-55860-258-5","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"49-54","msr_page_range_start":"49","msr_page_range_end":"54","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial 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