{"id":"https://openalex.org/W56894658","doi":null,"title":"Fast boosting using adversarial bandits","display_name":"Fast boosting using adversarial bandits","publication_year":2010,"publication_date":"2010-06-21","ids":{"openalex":"https://openalex.org/W56894658","mag":"56894658"},"language":"en","primary_location":{"id":"pmh:oai:HAL:in2p3-00614564v1","doi":null,"is_oa":true,"landing_page_url":"https://in2p3.hal.science/in2p3-00614564","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"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":"27th International Conference on Machine Learning (ICML 2010), Jun 2010, Haifa, Israel. pp.143-150","raw_type":"info:eu-repo/semantics/conferenceObject"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://in2p3.hal.science/in2p3-00614564","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047520070","display_name":"R\u00f3bert Busa\u2010Fekete","orcid":"https://orcid.org/0000-0002-3691-650X","observed_orcids":["https://orcid.org/0000-0002-3691-650X"]},"institutions":[{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404","https://openalex.org/I277688954"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I227486990","display_name":"University of Szeged","ror":"https://ror.org/01pnej532","country_code":"HU","type":"education","lineage":["https://openalex.org/I227486990"]},{"id":"https://openalex.org/I4210152167","display_name":"MTA-SZTE Research Group on Artificial Intelligence","ror":"https://ror.org/0507fk326","country_code":"HU","type":"facility","lineage":["https://openalex.org/I227486990","https://openalex.org/I4210152167","https://openalex.org/I7597260"]},{"id":"https://openalex.org/I7597260","display_name":"Hungarian Academy of Sciences","ror":"https://ror.org/02ks8qq67","country_code":"HU","type":"government","lineage":["https://openalex.org/I7597260"]}],"countries":["FR","HU"],"is_corresponding":false,"raw_author_name":"R\u00f3bert Busa\u2010Fekete","raw_affiliation_strings":["LAL/LRI, University of Paris-Sud, CNRS, Orsay, France Research Group on Artificial Intelligence of the Hungarian Academy of Sciences and University of Szeged, Szeged, Hungary#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LAL/LRI, University of Paris-Sud, CNRS, Orsay, France Research Group on Artificial Intelligence of the Hungarian Academy of Sciences and University of Szeged, Szeged, Hungary#TAB#","institution_ids":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I227486990","https://openalex.org/I4210152167","https://openalex.org/I7597260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051459492","display_name":"Bal\u00e1zs K\u00e9gl","orcid":"https://orcid.org/0000-0001-5610-1060","observed_orcids":["https://orcid.org/0000-0001-5610-1060"]},"institutions":[{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404","https://openalex.org/I277688954"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210144804","display_name":"Laboratoire de Recherche en Informatique","ror":"https://ror.org/04e3ktk27","country_code":"FR","type":"facility","lineage":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I277688954","https://openalex.org/I4210144804","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Bal\u00e1zs K\u00e9gl","raw_affiliation_strings":["LAL/LRI, University of Paris-Sud, CNRS, Orsay, France#TAB#"],"raw_orcid":"https://orcid.org/0000-0001-5610-1060","affiliations":[{"raw_affiliation_string":"LAL/LRI, University of Paris-Sud, CNRS, Orsay, France#TAB#","institution_ids":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I4210144804"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.6453,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.99001215,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":87,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"143","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9980000257492065,"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":0.9980000257492065,"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":0.0012000000569969416,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":9.999999747378752e-05,"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/adaboost","display_name":"AdaBoost","score":0.9240000247955322},{"id":"https://openalex.org/keywords/multi-armed-bandits","display_name":"multi-armed bandits","score":0.953000009059906},{"id":"https://openalex.org/keywords/adversarial-bandits","display_name":"adversarial bandits","score":0.9649999737739563},{"id":"https://openalex.org/keywords/boosting","display_name":"boosting","score":0.8270000219345093},{"id":"https://openalex.org/keywords/base-classifier-selection","display_name":"base classifier selection","score":0.8199999928474426},{"id":"https://openalex.org/keywords/computational-cost-reduction","display_name":"computational complexity reduction","score":0.8059999942779541},{"id":"https://openalex.org/keywords/sequential-decision-making","display_name":"sequential decision making","score":0.8109999895095825},{"id":"https://openalex.org/keywords/generalization-performance","display_name":"generalization performance","score":0.7239999771118164}],"concepts":[{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.8577996492385864},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7635430097579956},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7130566835403442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984381079673767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6337084770202637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5920522212982178},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5104073882102966},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37829580903053284}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:HAL:in2p3-00614564v1","doi":null,"is_oa":true,"landing_page_url":"https://in2p3.hal.science/in2p3-00614564","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"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":"27th International Conference on Machine Learning (ICML 2010), Jun 2010, Haifa, Israel. pp.143-150","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:56894658","doi":null,"is_oa":false,"landing_page_url":"https://hal.archives-ouvertes.fr/docs/00/61/45/64/PDF/Busa-Fekete.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Machine Learning","raw_type":null}],"best_oa_location":{"id":"pmh:oai:HAL:in2p3-00614564v1","doi":null,"is_oa":true,"landing_page_url":"https://in2p3.hal.science/in2p3-00614564","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"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":"27th International Conference on Machine Learning (ICML 2010), Jun 2010, Haifa, Israel. pp.143-150","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W3968525","https://openalex.org/W139579481","https://openalex.org/W305949787","https://openalex.org/W1504694836","https://openalex.org/W1570963478","https://openalex.org/W1988790447","https://openalex.org/W2032210760","https://openalex.org/W2072419029","https://openalex.org/W2077902449","https://openalex.org/W2105066050","https://openalex.org/W2108464053","https://openalex.org/W2113651538","https://openalex.org/W2122168905","https://openalex.org/W2125055259","https://openalex.org/W2132519943","https://openalex.org/W2142971854","https://openalex.org/W2153211312","https://openalex.org/W2154436219","https://openalex.org/W2168405694","https://openalex.org/W3097096317"],"related_works":["https://openalex.org/W7096528078","https://openalex.org/W7096569584","https://openalex.org/W3013997588","https://openalex.org/W2032326552","https://openalex.org/W2563972304","https://openalex.org/W1995055819","https://openalex.org/W4776547","https://openalex.org/W1155154084","https://openalex.org/W2171012768","https://openalex.org/W2151097972"],"abstract_inverted_index":{"In":[0],"this":[1,41,89,105],"paper":[2,106],"we":[3,113],"apply":[4],"multi-armed":[5],"bandits":[6],"(MABs)":[7],"to":[8,34,127,160],"improve":[9],"the":[10,36,63,71,74,80,94,98,135],"computational":[11,165],"complexity":[12],"of":[13,62,73,79,92,104,120,171],"AdaBoost.":[14],"AdaBoost":[15,85,162],"constructs":[16],"a":[17,21,47,60,108,129,139,143,156,164],"strong":[18],"classifier":[19,44,65,96],"in":[20,82,142],"stepwise":[22,42],"fashion":[23],"by":[24],"selecting":[25],"simple":[26],"base":[27,43,64,95],"classifiers":[28],"and":[29,51,76],"using":[30],"their":[31],"weighted":[32],"''vote''":[33],"determine":[35],"final":[37],"classification.":[38],"We":[39,146],"model":[40],"selection":[45],"as":[46],"sequential":[48],"decision":[49],"problem,":[50],"optimize":[52],"it":[53],"with":[54],"MABs":[55],"where":[56],"each":[57,83],"arm":[58],"represents":[59],"subset":[61,90],"set.":[66],"The":[67,101],"MAB":[68],"gradually":[69],"learns":[70],"''usefulness''":[72],"subsets,":[75],"selects":[77],"one":[78],"subsets":[81],"iteration.":[84],"then":[86],"searches":[87],"only":[88],"instead":[91,119],"optimizing":[93],"over":[97,107],"whole":[99],"space.":[100],"main":[102],"improvement":[103],"previous":[109],"approach":[110],"is":[111,168],"that":[112,134,151,167],"use":[114],"an":[115,169],"adversarial":[116],"bandit":[117],"algorithm":[118,141],"stochastic":[121],"bandits.":[122],"This":[123],"choice":[124],"allows":[125],"us":[126],"prove":[128],"weak-to-strong-learning":[130],"theorem,":[131],"which":[132],"means":[133],"proposed":[136],"technique":[137,153],"remains":[138],"boosting":[140],"formal":[144],"sense.":[145],"demonstrate":[147],"on":[148],"benchmark":[149],"datasets":[150],"our":[152],"can":[154],"achieve":[155],"generalization":[157],"performance":[158],"similar":[159],"standard":[161],"for":[163],"cost":[166],"order":[170],"magnitude":[172],"smaller.":[173]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":2}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2016-06-24T00:00:00"}
