{"id":"https://openalex.org/W2064211292","doi":"https://doi.org/10.1109/aipr.2013.6749332","title":"Combining the advice of experts with randomized boosting for robust pattern recognition","display_name":"Combining the advice of experts with randomized boosting for robust pattern recognition","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W2064211292","doi":"https://doi.org/10.1109/aipr.2013.6749332","mag":"2064211292"},"language":"en","primary_location":{"id":"doi:10.1109/aipr.2013.6749332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2013.6749332","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081306488","display_name":"Jing Peng","orcid":"https://orcid.org/0000-0002-9348-5638"},"institutions":[{"id":"https://openalex.org/I166088655","display_name":"Montclair State University","ror":"https://ror.org/01nxc2t48","country_code":"US","type":"education","lineage":["https://openalex.org/I166088655"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jing Peng","raw_affiliation_strings":["Computer Science Department, Montclair State University, Montclair, NJ","Computer Science Department, Montclair State University, Montclair, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Montclair State University, Montclair, NJ","institution_ids":["https://openalex.org/I166088655"]},{"raw_affiliation_string":"Computer Science Department, Montclair State University, Montclair, NJ, USA","institution_ids":["https://openalex.org/I166088655"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089593576","display_name":"Guna Seetharaman","orcid":null},"institutions":[{"id":"https://openalex.org/I1280414376","display_name":"United States Air Force Research Laboratory","ror":"https://ror.org/02e2egq70","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280414376","https://openalex.org/I1330347796","https://openalex.org/I4210102105","https://openalex.org/I4389425425"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guna Seetharaman","raw_affiliation_strings":["Information Directorate AFRL/RITB, Rome, NY","Inf. Directorate, AFRL/RITB, Rome, NY, USA"],"affiliations":[{"raw_affiliation_string":"Information Directorate AFRL/RITB, Rome, NY","institution_ids":["https://openalex.org/I1280414376"]},{"raw_affiliation_string":"Inf. Directorate, AFRL/RITB, Rome, NY, USA","institution_ids":["https://openalex.org/I1280414376"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081306488"],"corresponding_institution_ids":["https://openalex.org/I166088655"],"apc_list":null,"apc_paid":null,"fwci":0.37668844,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70532423,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9955999851226807,"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":0.7940362691879272},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.7054318189620972},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5853872895240784},{"id":"https://openalex.org/keywords/advice","display_name":"Advice (programming)","score":0.5661094188690186},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5574411153793335},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5470425486564636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49740079045295715},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43889135122299194},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.42748332023620605},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40094634890556335},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32904213666915894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7940362691879272},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.7054318189620972},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5853872895240784},{"id":"https://openalex.org/C2779955035","wikidata":"https://www.wikidata.org/wiki/Q4686785","display_name":"Advice (programming)","level":2,"score":0.5661094188690186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5574411153793335},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5470425486564636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49740079045295715},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43889135122299194},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.42748332023620605},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40094634890556335},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32904213666915894},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr.2013.6749332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2013.6749332","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W3968525","https://openalex.org/W28412257","https://openalex.org/W53987483","https://openalex.org/W56894658","https://openalex.org/W1532883599","https://openalex.org/W1540007258","https://openalex.org/W1570592793","https://openalex.org/W1570963478","https://openalex.org/W1578080815","https://openalex.org/W1602485673","https://openalex.org/W1603849545","https://openalex.org/W1988790447","https://openalex.org/W1998498767","https://openalex.org/W2013502943","https://openalex.org/W2016648380","https://openalex.org/W2032210760","https://openalex.org/W2048679005","https://openalex.org/W2067885219","https://openalex.org/W2073040595","https://openalex.org/W2077902449","https://openalex.org/W2104955141","https://openalex.org/W2105809105","https://openalex.org/W2108464053","https://openalex.org/W2124104513","https://openalex.org/W2126250169","https://openalex.org/W2132519943","https://openalex.org/W2133556223","https://openalex.org/W2137184539","https://openalex.org/W2142971854","https://openalex.org/W2145295623","https://openalex.org/W2148660279","https://openalex.org/W2151860489","https://openalex.org/W2154462399","https://openalex.org/W2158275940","https://openalex.org/W2160767978","https://openalex.org/W2166290812","https://openalex.org/W2168405694","https://openalex.org/W2172013605","https://openalex.org/W2912934387","https://openalex.org/W4212883601","https://openalex.org/W4244952642","https://openalex.org/W4253686195","https://openalex.org/W4285719527","https://openalex.org/W6602211964","https://openalex.org/W6632189861","https://openalex.org/W6634164890","https://openalex.org/W6635966985","https://openalex.org/W6641446668","https://openalex.org/W6653629126","https://openalex.org/W6675785006","https://openalex.org/W6678507914","https://openalex.org/W6679066655","https://openalex.org/W6682642966","https://openalex.org/W6683181193"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W3082059448","https://openalex.org/W4313640622"],"abstract_inverted_index":{"We":[0,211],"have":[1,46,79],"developed":[2,48],"an":[3,60,130],"algorithm,":[4],"called":[5,54],"ShareBoost,":[6,53],"for":[7,97,106,198,231],"combining":[8,199],"mulitple":[9],"classifiers":[10],"from":[11,29,226],"multiple":[12],"information":[13,229],"sources.":[14],"The":[15,87],"algorithm":[16,131,197,218],"offer":[17],"a":[18,49,83,93,107,177,195],"number":[19,84],"of":[20,52,85,89,95,139,157,202,223],"advantages,":[21],"such":[22],"as":[23,126],"increased":[24],"confidence":[25],"in":[26,66,82,176,187],"decision-making,":[27],"resulting":[28],"combined":[30],"complementary":[31],"data,":[32],"good":[33],"performance":[34],"against":[35],"noise,":[36],"and":[37,75,99,161,182,242],"the":[38,101,116,137,155,200,203,217,221,224],"ability":[39],"to":[40,70,123,129,165,205],"exploit":[41],"interplay":[42],"between":[43],"sensor":[44,104,159,178],"subspaces.We":[45],"also":[47],"randomized":[50],"version":[51],"rShare-Boost,":[55],"by":[56,115,132],"casting":[57],"ShareBoost":[58],"within":[59],"adversarial":[61],"multi-armed":[62],"bandit":[63],"framework.":[64],"This":[65],"turn":[67],"allows":[68],"us":[69],"show":[71,212],"rShareBoost":[72],"is":[73,92],"efficient":[74],"convergent.":[76],"Both":[77],"algorithms":[78,91],"shown":[80],"promise":[81],"applications.":[86],"hallmark":[88],"these":[90],"set":[94],"strategies":[96,111,125],"mining":[98],"exploiting":[100],"most":[102],"informative":[103],"sources":[105,230],"given":[108,128],"situation.":[109],"These":[110],"are":[112],"computations":[113],"performed":[114],"algorithms.":[117],"In":[118,136,190],"this":[119,191],"paper,":[120,192],"we":[121,193,236],"propose":[122],"consider":[124],"advice":[127,201,222],"\"experts\"":[133],"or":[134],"\"Oracle.\"":[135],"context":[138],"pattern":[140,146,208],"recognition,":[141],"there":[142],"can":[143],"be":[144,185],"several":[145],"recognition":[147,209],"strategies.":[148],"Each":[149,170],"strategy":[150,171],"makes":[151],"different":[152,163,174,180,188],"assumptions":[153],"regarding":[154],"fidelity":[156],"each":[158,183],"source":[160],"uses":[162],"data":[164,245],"arrive":[166],"at":[167,179],"its":[168],"estimates.":[169],"may":[172,184],"place":[173],"trust":[175],"times,":[181],"better":[186],"situations.":[189],"introduce":[194],"novel":[196],"experts":[204,225],"achieve":[206],"robust":[207],"performance.":[210],"that":[213,246],"with":[214],"high":[215],"probability":[216],"seeks":[219],"out":[220],"decision":[227],"relevant":[228],"making":[232],"optimal":[233],"prediction.":[234],"Finally,":[235],"provide":[237],"experimental":[238],"results":[239],"using":[240],"face":[241],"infrared":[243],"image":[244],"corroborate":[247],"our":[248],"theoretical":[249],"analysis.":[250]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
