{"id":"https://openalex.org/W3006746050","doi":"https://doi.org/10.1109/bigdata47090.2019.9005528","title":"A Bicameralism Voting Framework for Combining Knowledge from Clients into Better Prediction","display_name":"A Bicameralism Voting Framework for Combining Knowledge from Clients into Better Prediction","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3006746050","doi":"https://doi.org/10.1109/bigdata47090.2019.9005528","mag":"3006746050"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9005528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9005528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5047696782","display_name":"Yu-Tung Hsieh","orcid":"https://orcid.org/0000-0003-0655-1295"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yu-Tung Hsieh","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047572867","display_name":"Chuan-Yu Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chuan-Yu Lee","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064871646","display_name":"Ching\u2010Chi Lin","orcid":"https://orcid.org/0000-0002-9518-2809"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ching-Chi Lin","raw_affiliation_strings":["Academia Sinica, Institute of Information Science, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Academia Sinica, Institute of Information Science, Taipei, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057805207","display_name":"Pangfeng Liu","orcid":"https://orcid.org/0000-0002-5466-9960"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pangfeng Liu","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103369909","display_name":"Jan\u2010Jan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jan-Jan Wu","raw_affiliation_strings":["Academia Sinica, Institute of Information Science, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Academia Sinica, Institute of Information Science, Taipei, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5047696782"],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19657306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"298","last_page":"306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998000264167786,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998000264167786,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.816238522529602},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.801149845123291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.630744457244873},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5800621509552002},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4779527187347412},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3276059031486511}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.816238522529602},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.801149845123291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.630744457244873},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5800621509552002},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4779527187347412},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3276059031486511},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9005528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9005528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":87,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W304676660","https://openalex.org/W1565327149","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1882958252","https://openalex.org/W1946315329","https://openalex.org/W1995562189","https://openalex.org/W2053637704","https://openalex.org/W2067818689","https://openalex.org/W2097117768","https://openalex.org/W2115403315","https://openalex.org/W2128073546","https://openalex.org/W2149933564","https://openalex.org/W2152761983","https://openalex.org/W2159291411","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2214409633","https://openalex.org/W2257979135","https://openalex.org/W2269224708","https://openalex.org/W2274287116","https://openalex.org/W2283463896","https://openalex.org/W2395106899","https://openalex.org/W2471801048","https://openalex.org/W2522489477","https://openalex.org/W2526050071","https://openalex.org/W2531409750","https://openalex.org/W2535838896","https://openalex.org/W2591709446","https://openalex.org/W2618530766","https://openalex.org/W2751124354","https://openalex.org/W2766255512","https://openalex.org/W2766321325","https://openalex.org/W2766497195","https://openalex.org/W2777914285","https://openalex.org/W2788629937","https://openalex.org/W2886722183","https://openalex.org/W2900120080","https://openalex.org/W2903356604","https://openalex.org/W2912276085","https://openalex.org/W2949117887","https://openalex.org/W2951670162","https://openalex.org/W2952986481","https://openalex.org/W2954070046","https://openalex.org/W2963422767","https://openalex.org/W2963826681","https://openalex.org/W2964350391","https://openalex.org/W3038028469","https://openalex.org/W3098637454","https://openalex.org/W3105122387","https://openalex.org/W4297687186","https://openalex.org/W4298221930","https://openalex.org/W4299518610","https://openalex.org/W6610754620","https://openalex.org/W6633949838","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639480849","https://openalex.org/W6640486635","https://openalex.org/W6663928093","https://openalex.org/W6674914833","https://openalex.org/W6679154154","https://openalex.org/W6682132143","https://openalex.org/W6683633756","https://openalex.org/W6686164453","https://openalex.org/W6687483927","https://openalex.org/W6693628701","https://openalex.org/W6694260854","https://openalex.org/W6695838908","https://openalex.org/W6711850222","https://openalex.org/W6720275808","https://openalex.org/W6727252785","https://openalex.org/W6728184133","https://openalex.org/W6734231159","https://openalex.org/W6743716270","https://openalex.org/W6745253412","https://openalex.org/W6745794320","https://openalex.org/W6746720608","https://openalex.org/W6748263980","https://openalex.org/W6753725573","https://openalex.org/W6755988804","https://openalex.org/W6756840679","https://openalex.org/W6757266122","https://openalex.org/W6759226220","https://openalex.org/W6784995031","https://openalex.org/W6785591483"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0],"this":[1,138],"paper,":[2],"we":[3,18,27,45,55,79,112],"propose":[4,56],"a":[5,13,20,57,167,219,224,240],"bicameralism":[6,104,131,152,180,244,251],"voting":[7,105,132,153,181,245,252],"to":[8,30,206,222],"improve":[9,31],"the":[10,47,51,72,81,88,116,142,145,156,172,179,230,233,243,270],"accuracy":[11,143,150],"of":[12,118,144,151,166,175,257,261,267],"deep":[14,21,146],"learning":[15,22,147,213],"network.":[16],"After":[17],"train":[19,61,223],"network":[23],"with":[24,33,49,66,171,228],"existing":[25,190,209],"data,":[26,263],"may":[28],"want":[29],"it":[32,39,186],"some":[34],"newly":[35],"collected":[36,70],"data.":[37,53,177],"However,":[38],"would":[40],"be":[41,194],"time":[42],"consuming":[43],"if":[44],"retrain":[46],"model":[48,169,210,225,268],"all":[50],"available":[52],"Instead,":[54],"collective":[58,139],"framework":[59],"that":[60,165],"models":[62,86,119,271],"on":[63,155,218,274],"mobile":[64,73,89,121,276],"devices":[65],"new":[67,85,234],"data":[68,157,235],"(also":[69],"from":[71,83,87,108,120,226],"devices)":[74],"via":[75,100,211],"transfer":[76,212],"learning.":[77],"Then":[78],"collect":[80],"predictions":[82,95,99],"these":[84],"devices,":[90,122],"and":[91,192,232,264],"achieve":[92],"more":[93,238],"accurate":[94],"by":[96,127,198],"combining":[97],"their":[98],"voting.":[101],"The":[102,129,149],"proposed":[103,130],"is":[106,161,246],"different":[107,275],"federated":[109,249],"learning,":[110,250],"since":[111],"do":[113],"not":[114],"average":[115],"weights":[117],"but":[123,221],"let":[124],"them":[125],"vote":[126],"bicameralism.":[128],"mechanism":[133,140],"has":[134],"three":[135],"advantages.":[136],"First,":[137],"improves":[141],"model.":[148],"(VGG-19":[154],"set":[158],"Food-101":[159],"dataset)":[160],"77.838%,":[162],"higher":[163],"than":[164,239],"single":[168],"(75.517%)":[170],"same":[173],"amount":[174],"training":[176],"Second,":[178],"saves":[182],"computation":[183],"resource,":[184],"because":[185],"only":[187],"updates":[188],"an":[189,208],"model,":[191,258],"can":[193,253],"done":[195],"in":[196,203],"parallel":[197],"multiple":[199],"devices.":[200,277],"For":[201],"example,":[202],"our":[204],"experiments":[205],"update":[207],"takes":[214],"about":[215],"10":[216],"minutes":[217],"server,":[220],"scratch":[227],"both":[229],"original":[231],"will":[236],"take":[237],"week.":[241],"Finally,":[242],"flexible.":[247],"Unlike":[248],"use":[254],"any":[255,259,265],"architecture":[256],"preprocessing":[260],"input":[262],"format":[266],"when":[269],"are":[272],"trained":[273]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}