{"id":"https://openalex.org/W2782304201","doi":"https://doi.org/10.1109/tsp.2018.2839583","title":"Optimal Bayesian Transfer Learning","display_name":"Optimal Bayesian Transfer Learning","publication_year":2018,"publication_date":"2018-05-22","ids":{"openalex":"https://openalex.org/W2782304201","doi":"https://doi.org/10.1109/tsp.2018.2839583","mag":"2782304201"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2018.2839583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2018.2839583","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1801.00857","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Alireza Karbalayghareh","orcid":"https://orcid.org/0000-0002-4308-2582"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alireza Karbalayghareh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073946580","display_name":"Xiaoning Qian","orcid":"https://orcid.org/0000-0002-4347-2476"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoning Qian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112221423","display_name":"Edward R. Dougherty","orcid":null},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edward R. Dougherty","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":7.6157,"has_fulltext":true,"cited_by_count":82,"citation_normalized_percentile":{"value":0.97742998,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"66","issue":"14","first_page":"3724","last_page":"3739"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.9311000108718872,"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":0.7204560041427612},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6962911486625671},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6398358345031738},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6229043006896973},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5196862816810608},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.504269003868103},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.4557700753211975},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4431365430355072},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4280206859111786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204560041427612},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6962911486625671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6398358345031738},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6229043006896973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5196862816810608},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.504269003868103},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.4557700753211975},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4431365430355072},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4280206859111786}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2018.2839583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2018.2839583","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1801.00857","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.00857","pdf_url":"https://arxiv.org/pdf/1801.00857","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1801.00857","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.00857","pdf_url":"https://arxiv.org/pdf/1801.00857","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3936902016","display_name":null,"funder_award_id":"1553281","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4552275141","display_name":null,"funder_award_id":"CCF-1553281","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5557073858","display_name":null,"funder_award_id":"CCF-1553281","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2782304201.pdf","grobid_xml":"https://content.openalex.org/works/W2782304201.grobid-xml"},"referenced_works_count":68,"referenced_works":["https://openalex.org/W1565176903","https://openalex.org/W1576445103","https://openalex.org/W1594039573","https://openalex.org/W1677409904","https://openalex.org/W1722318740","https://openalex.org/W1731081199","https://openalex.org/W1834646128","https://openalex.org/W1835766057","https://openalex.org/W1942239643","https://openalex.org/W1970432641","https://openalex.org/W1972155227","https://openalex.org/W1982696459","https://openalex.org/W1985495956","https://openalex.org/W2009668020","https://openalex.org/W2032869812","https://openalex.org/W2035038062","https://openalex.org/W2077575889","https://openalex.org/W2120350343","https://openalex.org/W2122838776","https://openalex.org/W2134717973","https://openalex.org/W2149466042","https://openalex.org/W2158111773","https://openalex.org/W2159291411","https://openalex.org/W2159570078","https://openalex.org/W2160039895","https://openalex.org/W2164943005","https://openalex.org/W2165698076","https://openalex.org/W2166122445","https://openalex.org/W2166162270","https://openalex.org/W2168767290","https://openalex.org/W2279034837","https://openalex.org/W2311641197","https://openalex.org/W2395579298","https://openalex.org/W2422697180","https://openalex.org/W2436940381","https://openalex.org/W2513723748","https://openalex.org/W2530614786","https://openalex.org/W2547482843","https://openalex.org/W2548107131","https://openalex.org/W2558385255","https://openalex.org/W2582188783","https://openalex.org/W2590953969","https://openalex.org/W2596535143","https://openalex.org/W2682446068","https://openalex.org/W2766807258","https://openalex.org/W2767787532","https://openalex.org/W2778292275","https://openalex.org/W2789914388","https://openalex.org/W2795485111","https://openalex.org/W2950361018","https://openalex.org/W2951670162","https://openalex.org/W2952851926","https://openalex.org/W2963784072","https://openalex.org/W4237279480","https://openalex.org/W4295150927","https://openalex.org/W4362230038","https://openalex.org/W6633602821","https://openalex.org/W6634343353","https://openalex.org/W6637400245","https://openalex.org/W6637542466","https://openalex.org/W6637618735","https://openalex.org/W6638894083","https://openalex.org/W6681637710","https://openalex.org/W6683390231","https://openalex.org/W6683633756","https://openalex.org/W6695692224","https://openalex.org/W6720691552","https://openalex.org/W6733525777"],"related_works":["https://openalex.org/W3201126466","https://openalex.org/W4282827391","https://openalex.org/W3165580226","https://openalex.org/W2032094637","https://openalex.org/W2040227828","https://openalex.org/W2060045818","https://openalex.org/W2330406685","https://openalex.org/W2131935101","https://openalex.org/W856257623","https://openalex.org/W2892315154"],"abstract_inverted_index":{"Transfer":[0,163],"learning":[1,45,51,189],"has":[2],"recently":[3],"attracted":[4],"significant":[5],"research":[6],"attention,":[7],"as":[8],"it":[9],"simultaneously":[10],"learns":[11],"from":[12],"different":[13],"source":[14,55,101,117],"domains,":[15],"which":[16],"have":[17],"plenty":[18],"of":[19,66,72,79,94,115,151,180],"labeled":[20,33],"data,":[21],"and":[22,56,102,139,159,172,190],"transfers":[23,111],"the":[24,28,37,48,54,62,67,80,91,95,100,112,116,123,128,137,177,181,185],"relevant":[25],"knowledge":[26],"to":[27,35,105,119,155,184],"target":[29,57,103,124,129],"domain":[30,118,125,191],"with":[31,148],"limited":[32],"data":[34,175],"improve":[36],"prediction":[38],"performance.":[39],"We":[40,84],"propose":[41],"a":[42,86,108],"Bayesian":[43,162],"transfer":[44,50,188],"framework,":[46],"in":[47,99,122,134,145],"homogeneous":[49],"scenario,":[52],"where":[53],"domains":[58,104],"are":[59,143],"related":[60],"through":[61],"joint":[63,73,87],"prior":[64,74],"density":[65],"model":[68],"parameters.":[69],"The":[70],"modeling":[71],"densities":[75,142],"enables":[76],"better":[77],"understanding":[78],"\u201ctransferability\u201d":[81],"between":[82],"domains.":[83],"define":[85],"Wishart":[88],"distribution":[89],"for":[90],"precision":[92],"matrices":[93],"Gaussian":[96],"feature-label":[97],"distributions":[98],"act":[106],"like":[107],"bridge":[109],"that":[110],"useful":[113],"information":[114],"help":[120],"classification":[121],"by":[126],"improving":[127],"posteriors.":[130],"Using":[131],"several":[132],"theorems":[133],"multivariate":[135],"statistics,":[136],"posteriors":[138],"posterior":[140],"predictive":[141],"derived":[144],"closed":[146],"forms":[147],"hypergeometric":[149],"functions":[150],"matrix":[152],"argument,":[153],"leading":[154],"our":[156],"novel":[157],"closed-form":[158],"fast":[160],"Optimal":[161],"Learning":[164],"(OBTL)":[165],"classifier.":[166],"Experimental":[167],"results":[168],"on":[169],"both":[170],"synthetic":[171],"real-world":[173],"benchmark":[174],"confirm":[176],"superb":[178],"performance":[179],"OBTL":[182],"compared":[183],"other":[186],"state-of-the-art":[187],"adaptation":[192],"methods.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":5}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
