{"id":"https://openalex.org/W2741843808","doi":"https://doi.org/10.1109/icc.2017.7996912","title":"Non-Bayesian social learning with observation reuse and soft switching","display_name":"Non-Bayesian social learning with observation reuse and soft switching","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2741843808","doi":"https://doi.org/10.1109/icc.2017.7996912","mag":"2741843808"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2017.7996912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2017.7996912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103000008","display_name":"Md. Zulfiquar Ali Bhotto","orcid":"https://orcid.org/0000-0002-6492-1349"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Md. Zulfiquar Ali Bhotto","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore, SG"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore, SG","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046850399","display_name":"Wee Peng Tay","orcid":"https://orcid.org/0000-0002-1543-195X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wee Peng Tay","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9962000250816345,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9959999918937683,"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":0.7450565099716187},{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.7048299908638},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.6683494448661804},{"id":"https://openalex.org/keywords/social-learning","display_name":"Social learning","score":0.5911455154418945},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5857559442520142},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5803197622299194},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5770639181137085},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5758249163627625},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5743546485900879},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49907803535461426},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.09993106126785278}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7450565099716187},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.7048299908638},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.6683494448661804},{"id":"https://openalex.org/C79416737","wikidata":"https://www.wikidata.org/wiki/Q2305519","display_name":"Social learning","level":2,"score":0.5911455154418945},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5857559442520142},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5803197622299194},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5770639181137085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5758249163627625},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5743546485900879},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49907803535461426},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.09993106126785278},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2017.7996912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2017.7996912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1544576535","https://openalex.org/W1601684460","https://openalex.org/W1899340896","https://openalex.org/W1978009662","https://openalex.org/W1990970321","https://openalex.org/W2004525727","https://openalex.org/W2052602862","https://openalex.org/W2085222535","https://openalex.org/W2092214308","https://openalex.org/W2147153427","https://openalex.org/W2150746074","https://openalex.org/W2169826194","https://openalex.org/W2330981327","https://openalex.org/W3022273187","https://openalex.org/W4237964482","https://openalex.org/W4243330440"],"related_works":["https://openalex.org/W2000444236","https://openalex.org/W2384475851","https://openalex.org/W2353602216","https://openalex.org/W3208095355","https://openalex.org/W2367078749","https://openalex.org/W2381798600","https://openalex.org/W2028495302","https://openalex.org/W2351618306","https://openalex.org/W2133117170","https://openalex.org/W2999162218"],"abstract_inverted_index":{"A":[0],"recently":[1],"proposed":[2,141],"non-Bayesian":[3,156],"social":[4,44,73,115,157],"learning":[5,45,74,158],"rule":[6,12],"by":[7,47],"[1]":[8],"finds":[9],"an":[10,91],"update":[11,118],"that":[13,82,117,139],"achieves":[14],"the":[15,24,32,42,49,68,108,130,133,140],"least":[16],"Kullback-Leibler":[17],"(LKL)":[18],"divergence":[19],"between":[20,129],"a":[21,125],"proxy":[22],"of":[23,54,60,132],"true":[25],"distribution":[26],"generating":[27],"agent's":[28,33,62,87],"local":[29,63],"observations":[30,53],"and":[31,124,143],"beliefs.":[34],"In":[35],"this":[36,67],"paper,":[37],"we":[38,80,110],"investigate":[39],"improvements":[40,149],"to":[41,57,98,112],"LKL":[43,71],"algorithm":[46],"reusing":[48,70],"M":[50],"most":[51],"recent":[52],"each":[55,61],"agent":[56],"perform":[58],"updates":[59],"belief.":[64],"We":[65],"call":[66],"observation":[69],"(OR-LKL)":[72],"algorithm.":[75],"Under":[76],"some":[77],"technical":[78],"conditions,":[79],"show":[81],"under":[83],"OR-LKL":[84,142,145],"updates,":[85],"every":[86],"belief":[88],"concentrates":[89],"on":[90],"optimal":[92],"hypothesis":[93],"set.":[94],"Furthermore,":[95],"in":[96,107],"order":[97],"achieve":[99],"robust":[100,144],"performance":[101],"when":[102],"there":[103],"are":[104],"misinforming":[105],"agents":[106],"network,":[109],"propose":[111],"use":[113],"two":[114,134,151],"networks":[116],"their":[119],"beliefs":[120,131],"independently":[121],"using":[122],"OR-LKL,":[123],"soft":[126],"switching":[127],"mechanism":[128],"networks.":[135],"Simulation":[136],"results":[137],"demonstrate":[138],"algorithms":[146],"offer":[147],"significant":[148],"over":[150],"other":[152],"current":[153],"state-of-the":[154],"art":[155],"algorithms.":[159]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}