{"id":"https://openalex.org/W3028556448","doi":"https://doi.org/10.1145/3397271.3401069","title":"Accelerated Convergence for Counterfactual Learning to Rank","display_name":"Accelerated Convergence for Counterfactual Learning to Rank","publication_year":2020,"publication_date":"2020-07-25","ids":{"openalex":"https://openalex.org/W3028556448","doi":"https://doi.org/10.1145/3397271.3401069","mag":"3028556448"},"language":"en","primary_location":{"id":"doi:10.1145/3397271.3401069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2005.10615","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Rolf Jagerman","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135670","display_name":"Amsterdam University of the Arts","ror":"https://ror.org/04dde1554","country_code":"NL","type":"education","lineage":["https://openalex.org/I4210135670"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Rolf Jagerman","raw_affiliation_strings":["University of Amsterdam, Amsterdam, Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"]}]},{"author_position":"last","author":{"id":null,"display_name":"Maarten de Rijke","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112722","display_name":"Ahold Delhaize (Netherlands)","ror":"https://ror.org/01v6p2g18","country_code":"NL","type":"company","lineage":["https://openalex.org/I4210112722"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Maarten de Rijke","raw_affiliation_strings":["University of Amsterdam &amp; Ahold Delhaize, Amsterdam, Netherlands"],"affiliations":[{"raw_affiliation_string":"University of Amsterdam &amp; Ahold Delhaize, Amsterdam, Netherlands","institution_ids":["https://openalex.org/I4210112722","https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210135670","https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":1.6714,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.85257401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"469","last_page":"478"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9994000196456909,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9994000196456909,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973000288009644,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.926800012588501},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6492999792098999},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6431999802589417},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.6240000128746033},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5593000054359436},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5241000056266785},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.49149999022483826},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.39489999413490295}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.926800012588501},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6492999792098999},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6431999802589417},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.6240000128746033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5719000101089478},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5241000056266785},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49549999833106995},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.49149999022483826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4456999897956848},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.39489999413490295},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3869999945163727},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3416000008583069},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.3400000035762787},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32269999384880066},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C34585555","wikidata":"https://www.wikidata.org/wiki/Q1368723","display_name":"Learning curve","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C55479107","wikidata":"https://www.wikidata.org/wiki/Q97663916","display_name":"Stochastic approximation","level":3,"score":0.26159998774528503},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C2780551164","wikidata":"https://www.wikidata.org/wiki/Q2306599","display_name":"Column (typography)","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2533000111579895}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3397271.3401069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2005.10615","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.10615","pdf_url":"https://arxiv.org/pdf/2005.10615","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:dare.uva.nl:openaire/cd55e9df-543b-4dea-87c3-e90fd6b7ed9b","is_oa":true,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/accelerated-convergence-for-counterfactual-learning-to-rank(cd55e9df-543b-4dea-87c3-e90fd6b7ed9b).html","pdf_url":"https://pure.uva.nl/ws/files/53920784/jagerman_2020_accelerated.pdf","source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jagerman, R & de Rijke, M 2020, Accelerated Convergence for Counterfactual Learning to Rank. in SIGIR '20 : proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China. Association for Computing Machinery, New York, NY, pp. 469\u2013478, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25/07/20. https://doi.org/10.1145/3397271.3401069","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:uvapub:oai:dare.uva.nl:publications/cd55e9df-543b-4dea-87c3-e90fd6b7ed9b","is_oa":true,"landing_page_url":"https://dare.uva.nl/personal/pure/en/publications/accelerated-convergence-for-counterfactual-learning-to-rank(cd55e9df-543b-4dea-87c3-e90fd6b7ed9b).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2005.10615","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.10615","pdf_url":"https://arxiv.org/pdf/2005.10615","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2586376837","display_name":null,"funder_award_id":"612.001.551","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G629491556","display_name":null,"funder_award_id":"(NWO)","funder_id":"https://openalex.org/F4320321800","funder_display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321800","display_name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","ror":"https://ror.org/04jsz6e67"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1992549066","https://openalex.org/W2024859348","https://openalex.org/W2047221353","https://openalex.org/W2065221212","https://openalex.org/W2069870183","https://openalex.org/W2129160848","https://openalex.org/W2149427297","https://openalex.org/W2251567929","https://openalex.org/W2340526403","https://openalex.org/W2471222571","https://openalex.org/W2507134384","https://openalex.org/W2578241483","https://openalex.org/W2769473018","https://openalex.org/W2798855994","https://openalex.org/W2897183834","https://openalex.org/W2899259597","https://openalex.org/W2905569957","https://openalex.org/W2955421345","https://openalex.org/W2997842202","https://openalex.org/W3003609932","https://openalex.org/W3004599304","https://openalex.org/W4288280739"],"related_works":[],"abstract_inverted_index":{"Counterfactual":[0],"Learning":[1],"To":[2],"Rank":[3],"(LTR)":[4],"algorithms":[5],"learn":[6],"a":[7,17],"ranking":[8],"model":[9],"from":[10,58,103],"logged":[11,59],"user":[12,39,60],"interactions,":[13],"often":[14,41],"collected":[15],"using":[16],"production":[18],"system.":[19],"Employing":[20],"such":[21],"an":[22,31],"offline":[23],"learning":[24,57,76],"approach":[25],"has":[26],"many":[27],"benefits":[28],"compared":[29],"to":[30,54,74],"online":[32],"one,":[33],"but":[34],"it":[35],"is":[36,78,113],"challenging":[37],"as":[38],"feedback":[40],"contains":[42],"high":[43],"levels":[44],"of":[45,63,96],"bias.":[46],"Unbiased":[47],"LTR":[48],"uses":[49],"Inverse":[50],"Propensity":[51],"Scoring":[52],"(IPS)":[53],"enable":[55],"unbiased":[56],"interactions.":[61],"One":[62],"the":[64,79,84,93,104,109],"major":[65],"difficulties":[66],"in":[67],"applying":[68],"Stochastic":[69],"Gradient":[70],"Descent":[71],"(SGD)":[72],"approaches":[73,98],"counterfactual":[75],"problems":[77],"large":[80,105,119],"variance":[81,106],"introduced":[82,107],"by":[83,108],"propensity":[85],"weights.":[86,121],"In":[87],"this":[88],"paper":[89],"we":[90],"show":[91],"that":[92],"convergence":[94,112],"rate":[95],"SGD":[97],"with":[99],"IPS-weighted":[100],"gradients":[101],"suffers":[102],"IPS":[110,120],"weights:":[111],"slow,":[114],"especially":[115],"when":[116],"there":[117],"are":[118]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2020-05-29T00:00:00"}
