{"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/learning-with-abandonment","title":"Learning with Abandonment","arxiv_id":"1802.08718","date":"2018-02-23","proceeding":"ICML 2018 7","authors":["Ramesh Johari","Sven Schmit"],"abstract":"Consider a platform that wants to learn a personalized policy for each user,\nbut the platform faces the risk of a user abandoning the platform if she is\ndissatisfied with the actions of the platform. For example, a platform is\ninterested in personalizing the number of newsletters it sends, but faces the\nrisk that the user unsubscribes forever. We propose a general thresholded\nlearning model for scenarios like this, and discuss the structure of optimal\npolicies. We describe salient features of optimal personalization algorithms\nand how feedback the platform receives impacts the results. Furthermore, we\ninvestigate how the platform can efficiently learn the heterogeneity across\nusers by interacting with a population and provide performance guarantees.","url_abs":"http://arxiv.org/abs/1802.08718v1","url_pdf":"http://arxiv.org/pdf/1802.08718v1.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":"learning-with-abandonment","repo_url":"https://github.com/schmit/learning-abandonment","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}