{"id":"https://openalex.org/W4412403814","doi":"https://doi.org/10.26599/bdma.2025.9020028","title":"Large Deviation Algorithms for Thresholding Bandit Problem","display_name":"Large Deviation Algorithms for Thresholding Bandit Problem","publication_year":2025,"publication_date":"2025-07-14","ids":{"openalex":"https://openalex.org/W4412403814","doi":"https://doi.org/10.26599/bdma.2025.9020028"},"language":"en","primary_location":{"id":"doi:10.26599/bdma.2025.9020028","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2025.9020028","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.26599/bdma.2025.9020028","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074937383","display_name":"Manjing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Manjing Zhang","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ),Shenzhen,China,518107"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ),Shenzhen,China,518107","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047936273","display_name":"Guangwu Liu","orcid":"https://orcid.org/0009-0008-5975-2254"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]},{"id":"https://openalex.org/I4210133369","display_name":"Decision Sciences (United States)","ror":"https://ror.org/03gcvf773","country_code":"US","type":"company","lineage":["https://openalex.org/I4210133369"]}],"countries":["HK","US"],"is_corresponding":false,"raw_author_name":"Guangwu Liu","raw_affiliation_strings":["City University of Hong Kong,Department of Decision Analytics and Operations,Hong Kong,China,518057"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Decision Analytics and Operations,Hong Kong,China,518057","institution_ids":["https://openalex.org/I168719708","https://openalex.org/I4210133369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112213448","display_name":"Dai Shan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Dai","raw_affiliation_strings":["Shenzhen Research Institute of Big Data,Shenzhen,China,518172"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data,Shenzhen,China,518172","institution_ids":["https://openalex.org/I4210099586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434210","display_name":"Jiaqi Chen","orcid":"https://orcid.org/0009-0002-5126-3460"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Chen","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China,518060"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China,518060","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038682039","display_name":"Philippe Fournier\u2010Viger","orcid":"https://orcid.org/0000-0002-7680-9899"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Philippe Fournier-Viger","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China,518060"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,China,518060","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5074937383"],"corresponding_institution_ids":["https://openalex.org/I4210136793"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19079564,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"5","first_page":"1189","last_page":"1209"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9882000088691711,"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":0.9882000088691711,"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/T12288","display_name":"Optimization and Search Problems","score":0.9480000138282776,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9362000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.8130530118942261},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4751981496810913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.429006963968277},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4027012884616852},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3381173014640808},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10280856490135193}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8130530118942261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4751981496810913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.429006963968277},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4027012884616852},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3381173014640808},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10280856490135193}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.26599/bdma.2025.9020028","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2025.9020028","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2bc51fe8ffa242b99723e977a9a61613","is_oa":true,"landing_page_url":"https://doaj.org/article/2bc51fe8ffa242b99723e977a9a61613","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data Mining and Analytics, Vol 8, Iss 5, Pp 1189-1209 (2025)","raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:publications/e5648b0c-ea2e-4cb0-b6f8-6294b8d4cfcc","is_oa":true,"landing_page_url":"https://hdl.handle.net/2031/e5648b0c-ea2e-4cb0-b6f8-6294b8d4cfcc","pdf_url":null,"source":{"id":"https://openalex.org/S7407055387","display_name":"CityU Scholars","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Zhang, M, Liu, G, Dai, S, Chen, J & Fournier-Viger, P 2025, 'Large Deviation Algorithms for Thresholding Bandit Problem', Big Data Mining and Analytics, vol. 8, no. 5, pp. 1189-1209. https://doi.org/10.26599/BDMA.2025.9020028","raw_type":"article"}],"best_oa_location":{"id":"doi:10.26599/bdma.2025.9020028","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2025.9020028","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G198789539","display_name":null,"funder_award_id":"2023A1515011667","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6464829129","display_name":null,"funder_award_id":"2023B1515120020","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1516061453","https://openalex.org/W1554869488","https://openalex.org/W1972633005","https://openalex.org/W1998498767","https://openalex.org/W2000080679","https://openalex.org/W2009551863","https://openalex.org/W2023599408","https://openalex.org/W2036803464","https://openalex.org/W2069311504","https://openalex.org/W2168405694","https://openalex.org/W2606318404","https://openalex.org/W2912801008","https://openalex.org/W2965212020","https://openalex.org/W3080262031","https://openalex.org/W3093970103","https://openalex.org/W3121763331","https://openalex.org/W4210869902","https://openalex.org/W4212920552","https://openalex.org/W4238893454","https://openalex.org/W4246270964","https://openalex.org/W4389832104","https://openalex.org/W6604259001","https://openalex.org/W6632992360","https://openalex.org/W6638827766","https://openalex.org/W6674675285","https://openalex.org/W6675394771","https://openalex.org/W6678414246","https://openalex.org/W6681605418","https://openalex.org/W6681960134","https://openalex.org/W6688936716","https://openalex.org/W6713225123","https://openalex.org/W6736877702","https://openalex.org/W6743600924","https://openalex.org/W6745831847","https://openalex.org/W6762200027","https://openalex.org/W6767146217","https://openalex.org/W6775889919","https://openalex.org/W6801432716"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W1979597421","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W2106145857"],"abstract_inverted_index":{"The":[0],"Thresholding":[1],"Bandit":[2],"(TB)":[3],"problem":[4],"is":[5,87],"a":[6,22,32,68,91],"popular":[7],"sequential":[8],"decision-making":[9],"problem,":[10,64],"which":[11],"aims":[12],"at":[13],"identifying":[14],"the":[15,28,45,49,62,76,95,107],"systems":[16],"whose":[17],"means":[18],"are":[19,103],"greater":[20],"than":[21],"threshold.":[23],"Instead":[24],"of":[25,31,109,128],"working":[26],"on":[27],"upper":[29],"bound":[30],"loss":[33,46,129],"function,":[34],"our":[35,110],"approach":[36],"stands":[37],"out":[38],"from":[39],"conventional":[40],"practices":[41],"by":[42],"directly":[43],"minimizing":[44],"itself.":[47],"Leveraging":[48],"large":[50],"deviation":[51],"theory,":[52],"we":[53],"firstly":[54],"provide":[55],"an":[56],"asymptotically":[57],"optimal":[58],"allocation":[59,77],"rule":[60,78],"for":[61],"TB":[63],"and":[65,116,125],"then":[66],"propose":[67],"parameter-free":[69],"Large":[70,83],"Deviation":[71,84],"(LD)":[72],"algorithm":[73,86],"to":[74,93,105,113,121],"make":[75],"implementable.":[79],"Central":[80],"limit":[81],"theorem-based":[82],"(CLD)":[85],"further":[88],"proposed":[89],"as":[90],"supplement":[92],"improve":[94],"computation":[96],"efficiency":[97],"using":[98],"normal":[99],"approximation.":[100],"Extensive":[101],"experiments":[102],"conducted":[104],"validate":[106],"superiority":[108],"algorithms":[111],"compared":[112],"existing":[114],"methods,":[115],"demonstrate":[117],"their":[118],"broader":[119],"applications":[120],"more":[122],"general":[123],"distributions":[124],"various":[126],"kinds":[127],"functions.":[130]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}