{"id":"https://openalex.org/W4412377267","doi":"https://doi.org/10.1145/3726302.3729954","title":"Distributionally Robust Optimization for Unbiased Learning to Rank","display_name":"Distributionally Robust Optimization for Unbiased Learning to Rank","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412377267","doi":"https://doi.org/10.1145/3726302.3729954"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3729954","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729954","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729954","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729954","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102645619","display_name":"Zechun Niu","orcid":"https://orcid.org/0009-0009-7954-3713"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zechun Niu","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-7954-3713","affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102857942","display_name":"Lang Mei","orcid":"https://orcid.org/0000-0002-7960-3036"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lang Mei","raw_affiliation_strings":["Huawei Cloud BU, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7960-3036","affiliations":[{"raw_affiliation_string":"Huawei Cloud BU, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025013542","display_name":"Chong Chen","orcid":"https://orcid.org/0000-0003-1417-2295"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Chen","raw_affiliation_strings":["Huawei Cloud BU, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1417-2295","affiliations":[{"raw_affiliation_string":"Huawei Cloud BU, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072119199","display_name":"Jiaxin Mao","orcid":"https://orcid.org/0000-0002-9257-5498"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxin Mao","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9257-5498","affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07472817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2266","last_page":"2275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9952999949455261,"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"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9952999949455261,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9731000065803528,"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/computer-science","display_name":"Computer science","score":0.6105026602745056},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.569796085357666},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5446930527687073},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.48879119753837585},{"id":"https://openalex.org/keywords/robust-optimization","display_name":"Robust optimization","score":0.43113505840301514},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4166538715362549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3674653172492981},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.32791250944137573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3201477825641632},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24355563521385193},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.15243250131607056}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6105026602745056},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.569796085357666},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5446930527687073},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48879119753837585},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.43113505840301514},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4166538715362549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3674653172492981},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32791250944137573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3201477825641632},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24355563521385193},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.15243250131607056},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3726302.3729954","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729954","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729954","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3726302.3729954","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3729954","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3729954","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6620384876","display_name":null,"funder_award_id":"62377044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322499","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412377267.pdf","grobid_xml":"https://content.openalex.org/works/W4412377267.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1974360117","https://openalex.org/W1978259121","https://openalex.org/W1985554184","https://openalex.org/W1992549066","https://openalex.org/W2024932032","https://openalex.org/W2069870183","https://openalex.org/W2087131461","https://openalex.org/W2087818911","https://openalex.org/W2090883204","https://openalex.org/W2149427297","https://openalex.org/W2150291618","https://openalex.org/W2150593711","https://openalex.org/W2158195707","https://openalex.org/W2165698076","https://openalex.org/W2187089797","https://openalex.org/W2340526403","https://openalex.org/W2507134384","https://openalex.org/W2769473018","https://openalex.org/W2797400361","https://openalex.org/W2911802745","https://openalex.org/W2955421345","https://openalex.org/W3012600133","https://openalex.org/W3026200234","https://openalex.org/W3028135017","https://openalex.org/W3035119337","https://openalex.org/W3099404779","https://openalex.org/W3101148092","https://openalex.org/W3101935024","https://openalex.org/W3105712174","https://openalex.org/W3115087172","https://openalex.org/W3130740428","https://openalex.org/W3155345376","https://openalex.org/W4205807230","https://openalex.org/W4224317071","https://openalex.org/W4284975772","https://openalex.org/W4288079518","https://openalex.org/W4290877962","https://openalex.org/W4290878292","https://openalex.org/W4385573358","https://openalex.org/W4386729866","https://openalex.org/W4393968591","https://openalex.org/W4396735686","https://openalex.org/W4400530533","https://openalex.org/W6839314779"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W2560201613","https://openalex.org/W2002696586","https://openalex.org/W2772359885","https://openalex.org/W2793423758","https://openalex.org/W2899331914","https://openalex.org/W3011471740","https://openalex.org/W2954428433","https://openalex.org/W2572315477"],"abstract_inverted_index":{"Unbiased":[0],"learning":[1,95],"to":[2,10,46,96],"rank":[3,97],"(ULTR),":[4],"which":[5],"utilizes":[6],"historical":[7],"click":[8,35,121],"logs":[9],"train":[11],"ranking":[12,131],"models,":[13],"has":[14],"attracted":[15],"much":[16],"attention":[17],"in":[18,34],"the":[19,48,52,58,63,77,113,119,125,128,137,148],"IR":[20],"community.":[21],"Previous":[22],"studies":[23],"on":[24,28,147],"ULTR":[25,84,115],"have":[26],"focused":[27],"mitigating":[29],"a":[30,82],"variety":[31],"of":[32,51,105,139],"biases":[33],"logs,":[36],"such":[37],"as":[38],"position":[39],"bias,":[40,42,45],"trust":[41],"and":[43,66,75,124],"presentation":[44],"recover":[47],"true":[49],"relevance":[50],"query-document":[53],"pairs.":[54],"However,":[55],"they":[56],"overlooked":[57],"intrinsic":[59],"distribution":[60,78],"shifts":[61],"between":[62],"training":[64],"data":[65],"test":[67],"data.":[68],"In":[69],"this":[70,88],"paper,":[71],"we":[72,90,101,134],"first":[73],"validate":[74],"analyze":[76],"shift":[79],"problem":[80],"with":[81],"real-world":[83,149],"dataset.":[85,150],"To":[86],"solve":[87],"problem,":[89],"propose":[91],"distributionally":[92,107],"robust":[93,108],"unbiased":[94],"(DRO-ULTR)":[98],"methods.":[99],"Specifically,":[100],"design":[102],"two":[103],"kinds":[104],"group":[106],"optimization":[109],"(group-DRO)":[110],"frameworks":[111],"for":[112],"existing":[114],"methods,":[116],"one":[117],"using":[118,127],"pointwise":[120],"prediction":[122],"loss":[123],"other":[126],"listwise":[129],"counterfactual":[130],"loss.":[132],"Finally,":[133],"empirically":[135],"verify":[136],"effectiveness":[138],"our":[140],"DRO-ULTR":[141],"methods":[142],"by":[143],"conducting":[144],"extensive":[145],"experiments":[146]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}