{"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/training-a-subsampling-mechanism-in","title":"Training a Subsampling Mechanism in Expectation","arxiv_id":"1702.06914","date":"2017-02-22","proceeding":null,"authors":["Colin Raffel","Dieterich Lawson"],"abstract":"We describe a mechanism for subsampling sequences and show how to compute its\nexpected output so that it can be trained with standard backpropagation. We\ntest this approach on a simple toy problem and discuss its shortcomings.","url_abs":"http://arxiv.org/abs/1702.06914v3","url_pdf":"http://arxiv.org/pdf/1702.06914v3.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":"training-a-subsampling-mechanism-in","repo_url":"https://github.com/craffel/subsampling_in_expectation","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":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}