{"id":"https://openalex.org/W4327673755","doi":"https://doi.org/10.48550/arxiv.2303.08816","title":"Borda Regret Minimization for Generalized Linear Dueling Bandits","display_name":"Borda Regret Minimization for Generalized Linear Dueling Bandits","publication_year":2023,"publication_date":"2023-03-15","ids":{"openalex":"https://openalex.org/W4327673755","doi":"https://doi.org/10.48550/arxiv.2303.08816"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2303.08816","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.08816","pdf_url":"https://arxiv.org/pdf/2303.08816","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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2303.08816","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100458035","display_name":"Yue Wu","orcid":"https://orcid.org/0000-0002-4912-0092"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wu, Yue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100661557","display_name":"Tao Jin","orcid":"https://orcid.org/0000-0003-4668-0112"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Tao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114115163","display_name":"Hao Lou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lou, Hao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011621481","display_name":"Farzad Farnoud","orcid":"https://orcid.org/0000-0002-8684-4487"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Farnoud, Farzad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5051448391","display_name":"Quanquan Gu","orcid":"https://orcid.org/0000-0001-9830-793X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Quanquan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100458035"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9998999834060669,"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":0.9998999834060669,"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/T13553","display_name":"Age of Information Optimization","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.949999988079071,"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/regret","display_name":"Regret","score":0.9564566612243652},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5819575190544128},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44670143723487854},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4457882344722748},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43468955159187317},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4296499788761139},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3845990300178528},{"id":"https://openalex.org/keywords/mathematical-economics","display_name":"Mathematical economics","score":0.34678322076797485},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15333238244056702}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.9564566612243652},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5819575190544128},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44670143723487854},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4457882344722748},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43468955159187317},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4296499788761139},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3845990300178528},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.34678322076797485},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15333238244056702},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2303.08816","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.08816","pdf_url":"https://arxiv.org/pdf/2303.08816","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2303.08816","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2303.08816","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2303.08816","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.08816","pdf_url":"https://arxiv.org/pdf/2303.08816","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":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4327673755.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2971351794","https://openalex.org/W4376155396","https://openalex.org/W1947085858","https://openalex.org/W2174986909","https://openalex.org/W2527791220","https://openalex.org/W2101991911","https://openalex.org/W2155070487","https://openalex.org/W4311589891","https://openalex.org/W3123835761"],"abstract_inverted_index":{"Dueling":[0],"bandits":[1],"are":[2,163],"widely":[3],"used":[4],"to":[5,34,165],"model":[6,134],"preferential":[7],"feedback":[8],"prevalent":[9],"in":[10],"many":[11,61],"applications":[12],"such":[13],"as":[14],"recommendation":[15],"systems":[16],"and":[17,89,158],"ranking.":[18],"In":[19],"this":[20,97],"paper,":[21],"we":[22,100],"study":[23],"the":[24,36,39,45,76,84,92,107,127,132],"Borda":[25,41,77],"regret":[26,68,78,115],"minimization":[27,79],"problem":[28],"for":[29,75,106,126],"dueling":[30,56],"bandits,":[31],"which":[32,59,110,148],"aims":[33],"identify":[35],"item":[37],"with":[38],"highest":[40],"score":[42],"while":[43],"minimizing":[44],"cumulative":[46],"regret.":[47],"We":[48,64,120],"propose":[49,101,122],"a":[50,67,112,159],"rich":[51],"class":[52],"of":[53,71,86],"generalized":[54],"linear":[55,129],"bandit":[57],"models,":[58],"cover":[60],"existing":[62],"models.":[63],"first":[65],"prove":[66],"lower":[69,98],"bound":[70,117],"order":[72],"$\u03a9(d^{2/3}":[73],"T^{2/3})$":[74,146],"problem,":[80],"where":[81,131],"$d$":[82],"is":[83,91,149],"dimension":[85],"contextual":[87],"vectors":[88],"$T$":[90],"time":[93],"horizon.":[94],"To":[95],"attain":[96],"bound,":[99],"an":[102,123,144],"explore-then-commit":[103],"type":[104],"algorithm":[105,125,142],"stochastic":[108],"setting,":[109,130],"has":[111],"nearly":[113],"matching":[114],"upper":[116],"$\\tilde{O}(d^{2/3}":[118,145],"T^{2/3})$.":[119],"also":[121,150],"EXP3-type":[124],"adversarial":[128],"underlying":[133],"parameter":[135],"can":[136],"change":[137],"at":[138],"each":[139],"round.":[140],"Our":[141],"achieves":[143],"regret,":[147],"optimal.":[151],"Empirical":[152],"evaluations":[153],"on":[154],"both":[155],"synthetic":[156],"data":[157],"simulated":[160],"real-world":[161],"environment":[162],"conducted":[164],"corroborate":[166],"our":[167],"theoretical":[168],"analysis.":[169]},"counts_by_year":[],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}