{"id":"https://openalex.org/W7133201854","doi":"https://doi.org/10.52202/075280-0579","title":"Delegated Classification","display_name":"Delegated Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W7133201854","doi":"https://doi.org/10.52202/075280-0579"},"language":"en","primary_location":{"id":"doi:10.52202/075280-0579","doi":"https://doi.org/10.52202/075280-0579","is_oa":false,"landing_page_url":"https://doi.org/10.52202/075280-0579","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Neural Information Processing Systems 36","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.11475","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025499401","display_name":"Eden Saig","orcid":"https://orcid.org/0000-0002-0810-2218","observed_orcids":["https://orcid.org/0000-0002-0810-2218"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eden Saig","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081600081","display_name":"Inbal Talgam-Cohen","orcid":"https://orcid.org/0000-0002-2838-3264","observed_orcids":["https://orcid.org/0000-0002-2838-3264"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Inbal Talgam-Cohen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061734145","display_name":"Nir Rosenfeld","orcid":"https://orcid.org/0000-0002-4334-2508","observed_orcids":["https://orcid.org/0000-0002-4334-2508"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nir Rosenfeld","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9067,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.87436107,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"13200","last_page":"13236"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11031","display_name":"Game Theory and Applications","score":0.5015000104904175,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11031","display_name":"Game Theory and Applications","score":0.5015000104904175,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.13840000331401825,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.09080000221729279,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/incentive-compatibility","display_name":"incentive compatibility","score":0.5109999775886536},{"id":"https://openalex.org/keywords/principal-agent-games","display_name":"principal-agent games","score":0.8180000185966492},{"id":"https://openalex.org/keywords/contract-design","display_name":"contract design","score":0.7919999957084656},{"id":"https://openalex.org/keywords/neyman-pearson-lemma","display_name":"Neyman-Pearson lemma","score":0.9330000281333923},{"id":"https://openalex.org/keywords/hypothesis-testing","display_name":"hypothesis testing","score":0.8460000157356262},{"id":"https://openalex.org/keywords/conflict-of-interest","display_name":"conflicts of interest","score":0.7799999713897705},{"id":"https://openalex.org/keywords/learning-curve","display_name":"learning curve","score":0.6169999837875366},{"id":"https://openalex.org/keywords/scaling-laws","display_name":"scaling laws","score":0.9610000252723694},{"id":"https://openalex.org/keywords/binary-classification","display_name":"binary classification","score":0.5509999990463257}],"concepts":[{"id":"https://openalex.org/C86532276","wikidata":"https://www.wikidata.org/wiki/Q1184065","display_name":"Delegation","level":2,"score":0.762499988079071},{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.6015999913215637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5611000061035156},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5579000115394592},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49070000648498535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4214000105857849},{"id":"https://openalex.org/C13355873","wikidata":"https://www.wikidata.org/wiki/Q2920850","display_name":"Connection (principal bundle)","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C2779915298","wikidata":"https://www.wikidata.org/wiki/Q7604400","display_name":"Statistical learning theory","level":3,"score":0.3537999987602234},{"id":"https://openalex.org/C79301358","wikidata":"https://www.wikidata.org/wiki/Q1918846","display_name":"Contract theory","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C34585555","wikidata":"https://www.wikidata.org/wiki/Q1368723","display_name":"Learning curve","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C50292564","wikidata":"https://www.wikidata.org/wiki/Q2462783","display_name":"Computational learning theory","level":3,"score":0.2973000109195709},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C200707436","wikidata":"https://www.wikidata.org/wiki/Q1053211","display_name":"Principal\u2013agent problem","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C153517567","wikidata":"https://www.wikidata.org/wiki/Q26090","display_name":"Mechanism design","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2587999999523163}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.52202/075280-0579","doi":"https://doi.org/10.52202/075280-0579","is_oa":false,"landing_page_url":"https://doi.org/10.52202/075280-0579","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Neural Information Processing Systems 36","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2306.11475","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.11475","pdf_url":"https://arxiv.org/pdf/2306.11475","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2306.11475","doi":"https://doi.org/10.48550/arxiv.2306.11475","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.11475","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2306.11475","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.11475","pdf_url":"https://arxiv.org/pdf/2306.11475","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320323278","display_name":"Council for Higher Education","ror":"https://ror.org/036mqp197"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7133201854.pdf","grobid_xml":"https://content.openalex.org/works/W7133201854.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W3001279689","https://openalex.org/W3126894933","https://openalex.org/W4280649288","https://openalex.org/W4302012920","https://openalex.org/W4383558041","https://openalex.org/W4386557251"],"related_works":["https://openalex.org/W4386557251","https://openalex.org/W2136134199","https://openalex.org/W7221799010","https://openalex.org/W7133245209","https://openalex.org/W4400373528","https://openalex.org/W4240035324","https://openalex.org/W4387046202","https://openalex.org/W2901483911","https://openalex.org/W2433154113","https://openalex.org/W4386251589"],"abstract_inverted_index":{"When":[0],"machine":[1,31],"learning":[2,32,44,128],"is":[3,88],"outsourced":[4],"to":[5,61,90,93],"a":[6,24,38,72,99],"rational":[7],"agent,":[8],"conflicts":[9],"of":[10,30,58,85,127],"interest":[11],"might":[12],"arise":[13],"and":[14,68,105,130,134,141],"severely":[15],"impact":[16],"predictive":[17],"performance.":[18],"In":[19,79],"this":[20,62],"work,":[21],"we":[22,64,110],"propose":[23],"theoretical":[25],"framework":[26],"for":[27],"incentive-aware":[28],"delegation":[29,36],"tasks.":[33,144],"We":[34],"model":[35],"as":[37],"principal-agent":[39],"game,":[40],"in":[41,124],"which":[42],"accurate":[43],"can":[45,115],"be":[46,91,116],"incentivized":[47],"by":[48],"the":[49,55,80,83,94,125],"principal":[50],"using":[51,118,139],"performance-based":[52],"contracts.":[53],"Adapting":[54],"economic":[56,135],"theory":[57],"contract":[59,103],"design":[60,104],"setting,":[63],"define":[65],"budget-optimal":[66,113],"contracts":[67,87,114],"prove":[69],"they":[70],"take":[71],"simple":[73],"threshold":[74],"form":[75],"under":[76],"reasonable":[77],"assumptions.":[78],"binary-action":[81],"case,":[82],"optimality":[84],"such":[86],"shown":[89],"equivalent":[92],"classic":[95],"Neyman-Pearson":[96],"lemma,":[97],"establishing":[98],"formal":[100],"connection":[101],"between":[102],"statistical":[106],"hypothesis":[107],"testing.":[108],"Empirically,":[109],"demonstrate":[111],"that":[112],"constructed":[117],"small-scale":[119],"data,":[120],"leveraging":[121],"recent":[122],"advances":[123],"study":[126],"curves":[129],"scaling":[131],"laws.":[132],"Performance":[133],"outcomes":[136],"are":[137],"evaluated":[138],"synthetic":[140],"real-world":[142],"classification":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-03-03T00:00:00"}
