{"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/the-diverse-cohort-selection-problem","title":"The Diverse Cohort Selection Problem","arxiv_id":"1709.03441","date":"2017-09-11","proceeding":null,"authors":["Candice Schumann","Samsara N. Counts","Jeffrey S. Foster","John P. Dickerson"],"abstract":"How should a firm allocate its limited interviewing resources to select the\noptimal cohort of new employees from a large set of job applicants? How should\nthat firm allocate cheap but noisy resume screenings and expensive but in-depth\nin-person interviews? We view this problem through the lens of combinatorial\npure exploration (CPE) in the multi-armed bandit setting, where a central\nlearning agent performs costly exploration of a set of arms before selecting a\nfinal subset with some combinatorial structure. We generalize a recent CPE\nalgorithm to the setting where arm pulls can have different costs and return\ndifferent levels of information. We then prove theoretical upper bounds for a\ngeneral class of arm-pulling strategies in this new setting. We apply our\ngeneral algorithm to a real-world problem with combinatorial structure:\nincorporating diversity into university admissions. We take real data from\nadmissions at one of the largest US-based computer science graduate programs\nand show that a simulation of our algorithm produces a cohort with hiring\noverall utility while spending comparable budget to the current admissions\nprocess at that university.","url_abs":"http://arxiv.org/abs/1709.03441v5","url_pdf":"http://arxiv.org/pdf/1709.03441v5.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":"the-diverse-cohort-selection-problem","repo_url":"https://github.com/principledhiring/SWAP","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1709.03441","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}